# Serialized Form

- ## Package weka.associations

  - ### Class weka.associations.AbstractAssociator

    class AbstractAssociator extends Object implements Serializable
    serialVersionUID:
      -3017644543382432070L

    - #### Serialized Fields

      - ##### m_DoNotCheckCapabilities

            boolean m_DoNotCheckCapabilities

        Whether capabilities should not be checked

  - ### Class weka.associations.Apriori

    class Apriori extends AbstractAssociator implements Serializable
    serialVersionUID:
      3277498842319212687L

    - #### Serialized Fields

      - ##### m_allTheRules

            ArrayList<Object>[] m_allTheRules

        The list of all generated rules.

      - ##### m_car

            boolean m_car

        Flag indicating whether class association rules are mined.

      - ##### m_classIndex

            int m_classIndex

        The class index.

      - ##### m_cycles

            int m_cycles

        Number of cycles used before required number of rules was one.

      - ##### m_delta

            double m_delta

        Delta by which m_minSupport is decreased in each iteration.

      - ##### m_hashtables

            ArrayList<Hashtable<ItemSet,Integer>> m_hashtables

        The same information stored in hash tables.

      - ##### m_instances

            Instances m_instances

        The instances (transactions) to be used for generating the association rules.

      - ##### m_lowerBoundMinSupport

            double m_lowerBoundMinSupport

        The lower bound for the minimum support.

      - ##### m_Ls

            ArrayList<ArrayList<Object>> m_Ls

        The set of all sets of itemsets L.

      - ##### m_metricType

            int m_metricType

        The selected metric type.

      - ##### m_minMetric

            double m_minMetric

        The minimum metric score.

      - ##### m_minSupport

            double m_minSupport

        The minimum support.

      - ##### m_numRules

            int m_numRules

        The maximum number of rules that are output.

      - ##### m_onlyClass

            Instances m_onlyClass

        Only the class attribute of all Instances.

      - ##### m_outputItemSets

            boolean m_outputItemSets

        Output itemsets found?

      - ##### m_removeMissingCols

            boolean m_removeMissingCols

        Remove columns with all missing values

      - ##### m_significanceLevel

            double m_significanceLevel

        Significance level for optional significance test.

      - ##### m_toStringDelimiters

            String m_toStringDelimiters

        ToString delimiters, if any

      - ##### m_treatZeroAsMissing

            boolean m_treatZeroAsMissing

        Treat zeros as missing (rather than a value in their own right)

      - ##### m_upperBoundMinSupport

            double m_upperBoundMinSupport

        The upper bound on the support

      - ##### m_verbose

            boolean m_verbose

        Report progress iteratively

  - ### Class weka.associations.AprioriItemSet

    class AprioriItemSet extends ItemSet implements Serializable
    serialVersionUID:
      7684467755712672058L

  - ### Class weka.associations.AssociationRules

    class AssociationRules extends Object implements Serializable
    serialVersionUID:
      8889198755948056749L

    - #### Serialized Fields

      - ##### m_producer

            String m_producer

        The scheme that produced these rules

      - ##### m_rules

            List<AssociationRule> m_rules

        The list of rules

  - ### Class weka.associations.BinaryItem

    class BinaryItem extends NominalItem implements Serializable
    serialVersionUID:
      -3372941834914147669L

  - ### Class weka.associations.DefaultAssociationRule

    class DefaultAssociationRule extends AssociationRule implements Serializable
    serialVersionUID:
      -661269018702294489L

    - #### Serialized Fields

      - ##### m_consequence

            Collection<Item> m_consequence

        The consequence of the rule

      - ##### m_consequenceSupport

            int m_consequenceSupport

        The support for the consequence

      - ##### m_metricType

            DefaultAssociationRule.METRIC_TYPE m_metricType

        The metric type for this rule

      - ##### m_premise

            Collection<Item> m_premise

        The premise of the rule

      - ##### m_premiseSupport

            int m_premiseSupport

        The support for the premise

      - ##### m_totalSupport

            int m_totalSupport

        The total support for the item set (premise + consequence)

      - ##### m_totalTransactions

            int m_totalTransactions

        The total number of transactions in the data

  - ### Class weka.associations.FilteredAssociationRules

    class FilteredAssociationRules extends AssociationRules implements Serializable
    serialVersionUID:
      -4223408305476916955L

    - #### Serialized Fields

      - ##### m_filter

            Filter m_filter

      - ##### m_wrappedRules

            AssociationRules m_wrappedRules

  - ### Class weka.associations.FilteredAssociator

    class FilteredAssociator extends SingleAssociatorEnhancer implements Serializable
    serialVersionUID:
      -4523450618538717400L

    - #### Serialized Fields

      - ##### m_ClassIndex

            int m_ClassIndex

        The class index.

      - ##### m_Filter

            Filter m_Filter

        The filter

      - ##### m_FilteredInstances

            Instances m_FilteredInstances

        The instance structure of the filtered instances

  - ### Class weka.associations.FPGrowth

    class FPGrowth extends AbstractAssociator implements Serializable
    serialVersionUID:
      3620717108603442911L

    - #### Serialized Fields

      - ##### m_delta

            double m_delta

        The amount by which to decrease the support in each iteration

      - ##### m_findAllRulesForSupportLevel

            boolean m_findAllRulesForSupportLevel

        If true, just all rules meeting the lower bound on the minimum support will be found. The number of rules to find will be ignored and the iterative reduction of support will not be done.

      - ##### m_largeItemSets

            weka.associations.FPGrowth.FrequentItemSets m_largeItemSets

        Holds the large item sets found

      - ##### m_lowerBoundMinSupport

            double m_lowerBoundMinSupport

        The lower bound on minimum support

      - ##### m_maxItems

            int m_maxItems

      - ##### m_metric

            DefaultAssociationRule.METRIC_TYPE m_metric

      - ##### m_metricThreshold

            double m_metricThreshold

      - ##### m_mustContainOR

            boolean m_mustContainOR

        Use OR rather than AND when considering must contain lists

      - ##### m_numInstances

            int m_numInstances

        The number of instances in the data

      - ##### m_numRulesToFind

            int m_numRulesToFind

        The number of rules to find

      - ##### m_offDiskReportingFrequency

            int m_offDiskReportingFrequency

        When processing data off of disk report progress this frequently (number of instances).

      - ##### m_positiveIndex

            int m_positiveIndex

        The index (1 based) of binary attributes to treat as the positive value

      - ##### m_rules

            List<AssociationRule> m_rules

        Holds the rules

      - ##### m_rulesMustContain

            String m_rulesMustContain

        If set, then only output rules containing these itmes

      - ##### m_transactionsMustContain

            String m_transactionsMustContain

        If set, limit the transactions (instances) input to the algorithm to those that contain these items

      - ##### m_upperBoundMinSupport

            double m_upperBoundMinSupport

        The upper bound on the minimum support

  - ### Class weka.associations.FPGrowth.FPTreeNode

    class FPTreeNode extends Object implements Serializable
    serialVersionUID:
      4396315323673737660L

    - #### Serialized Fields

      - ##### m_children

            Map<BinaryItem,weka.associations.FPGrowth.FPTreeNode> m_children

        the children of this node

      - ##### m_ID

            int m_ID

        ID (for graphing the tree)

      - ##### m_item

            BinaryItem m_item

        item at this node

      - ##### m_levelSibling

            weka.associations.FPGrowth.FPTreeNode m_levelSibling

        link to another sibling at this level in the tree

      - ##### m_parent

            weka.associations.FPGrowth.FPTreeNode m_parent

        link to the parent node

      - ##### m_projectedCounts

            weka.associations.FPGrowth.ShadowCounts m_projectedCounts

        counts associated with projected versions of this node

  - ### Class weka.associations.FPGrowth.FPTreeRoot.Header

    class Header extends Object implements Serializable
    serialVersionUID:
      -6583156284891368909L

    - #### Serialized Fields

      - ##### m_headerList

            List<weka.associations.FPGrowth.FPTreeNode> m_headerList

        The list of pointers into the tree structure

      - ##### m_projectedHeaderCounts

            weka.associations.FPGrowth.ShadowCounts m_projectedHeaderCounts

        Projected header counts for this entry

  - ### Class weka.associations.FPGrowth.FrequentBinaryItemSet

    class FrequentBinaryItemSet extends Object implements Serializable
    serialVersionUID:
      -6543815873565829448L

    - #### Serialized Fields

      - ##### m_items

            ArrayList<BinaryItem> m_items

        The list of items in the item set

      - ##### m_support

            int m_support

        the support of this item set

  - ### Class weka.associations.FPGrowth.FrequentItemSets

    class FrequentItemSets extends Object implements Serializable
    serialVersionUID:
      4173606872363973588L

    - #### Serialized Fields

      - ##### m_numberOfTransactions

            int m_numberOfTransactions

        The total number of transactions in the data

      - ##### m_sets

            ArrayList<weka.associations.FPGrowth.FrequentBinaryItemSet> m_sets

        The list of frequent item sets

  - ### Class weka.associations.FPGrowth.ShadowCounts

    class ShadowCounts extends Object implements Serializable
    serialVersionUID:
      4435433714185969155L

    - #### Serialized Fields

      - ##### m_counts

            ArrayList<Integer> m_counts

        Holds the counts at different recursion levels

  - ### Class weka.associations.Item

    class Item extends Object implements Serializable
    serialVersionUID:
      -430198211081183575L

    - #### Serialized Fields

      - ##### m_attribute

            Attribute m_attribute

        The attribute that backs this item

      - ##### m_frequency

            int m_frequency

        The frequency of this item

  - ### Class weka.associations.ItemSet

    class ItemSet extends Object implements Serializable
    serialVersionUID:
      2724000045282835791L

    - #### Serialized Fields

      - ##### m_counter

            int m_counter

        Counter for how many transactions contain this item set.

      - ##### m_items

            int[] m_items

        The items stored as an array of of ints.

      - ##### m_secondaryCounter

            int m_secondaryCounter

        Holds support of consequence only in the case where this ItemSet is a consequence of a rule (as m_counter in this case actually holds the support of the rule as a whole, i.e. premise and consequence)

      - ##### m_totalTransactions

            int m_totalTransactions

        The total number of transactions

  - ### Class weka.associations.LabeledItemSet

    class LabeledItemSet extends ItemSet implements Serializable
    serialVersionUID:
      4158771925518299903L

    - #### Serialized Fields

      - ##### m_classLabel

            int m_classLabel

        The class label.

      - ##### m_ruleSupCounter

            int m_ruleSupCounter

        The support of the rule.

  - ### Class weka.associations.NominalItem

    class NominalItem extends Item implements Serializable
    serialVersionUID:
      2182122099990462066L

    - #### Serialized Fields

      - ##### m_valueIndex

            int m_valueIndex

        The index of the value considered to be positive

  - ### Class weka.associations.NumericItem

    class NumericItem extends Item implements Serializable
    serialVersionUID:
      -7869433770765864800L

    - #### Serialized Fields

      - ##### m_comparison

            NumericItem.Comparison m_comparison

        The comparison operator

      - ##### m_splitPoint

            double m_splitPoint

        The numeric test

  - ### Class weka.associations.SingleAssociatorEnhancer

    class SingleAssociatorEnhancer extends AbstractAssociator implements Serializable
    serialVersionUID:
      -3665885256363525164L

    - #### Serialized Fields

      - ##### m_Associator

            Associator m_Associator

        The base associator to use

- ## Package weka.attributeSelection

  - ### Class weka.attributeSelection.ASEvaluation

    class ASEvaluation extends Object implements Serializable
    serialVersionUID:
      2091705669885950849L

    - #### Serialized Fields

      - ##### m_DoNotCheckCapabilities

            boolean m_DoNotCheckCapabilities

        Whether capabilities should not be checked

  - ### Class weka.attributeSelection.ASSearch

    class ASSearch extends Object implements Serializable
    serialVersionUID:
      7591673350342236548L

  - ### Class weka.attributeSelection.AttributeSelection

    class AttributeSelection extends Object implements Serializable
    serialVersionUID:
      4170171824147584330L

    - #### Serialized Fields

      - ##### m_ASEvaluator

            ASEvaluation m_ASEvaluator

        the attribute/subset evaluator

      - ##### m_attributeFilter

            Remove m_attributeFilter

        the attribute filter for processing instances with respect to the most recent feature selection run

      - ##### m_attributeRanking

            double[][] m_attributeRanking

        the attribute indexes and associated merits if a ranking is produced

      - ##### m_doRank

            boolean m_doRank

        rank features (if allowed by the search method)

      - ##### m_doXval

            boolean m_doXval

        do cross validation

      - ##### m_numFolds

            int m_numFolds

        the number of folds to use for cross validation

      - ##### m_numToSelect

            int m_numToSelect

        number of attributes requested from ranked results

      - ##### m_rankResults

            double[][] m_rankResults

        hold statistics for repeated feature selection, such as under cross validation

      - ##### m_searchMethod

            ASSearch m_searchMethod

        the search method

      - ##### m_seed

            int m_seed

        seed used to randomly shuffle instances for cross validation

      - ##### m_selectedAttributeSet

            int[] m_selectedAttributeSet

        the selected attributes

      - ##### m_selectionResults

            StringBuffer m_selectionResults

        holds a string describing the results of the attribute selection

      - ##### m_subsetResults

            double[] m_subsetResults

      - ##### m_trainInstances

            Instances m_trainInstances

        the instances to select attributes from

      - ##### m_transformer

            AttributeTransformer m_transformer

        if a feature selection run involves an attribute transformer

  - ### Class weka.attributeSelection.AttributeSetEvaluator

    class AttributeSetEvaluator extends ASEvaluation implements Serializable
    serialVersionUID:
      -5744881009422257389L

  - ### Class weka.attributeSelection.BestFirst

    class BestFirst extends ASSearch implements Serializable
    serialVersionUID:
      7841338689536821867L

    - #### Serialized Fields

      - ##### m_bestMerit

            double m_bestMerit

        holds the merit of the best subset found

      - ##### m_cacheSize

            int m_cacheSize

        holds the maximum size of the lookup cache for evaluated subsets

      - ##### m_classIndex

            int m_classIndex

        holds the class index

      - ##### m_debug

            boolean m_debug

        for debugging

      - ##### m_hasClass

            boolean m_hasClass

        does the data have a class

      - ##### m_maxStale

            int m_maxStale

        maximum number of stale nodes before terminating search

      - ##### m_numAttribs

            int m_numAttribs

        number of attributes in the data

      - ##### m_searchDirection

            int m_searchDirection

        0 == backward search, 1 == forward search, 2 == bidirectional

      - ##### m_starting

            int[] m_starting

        holds an array of starting attributes

      - ##### m_startRange

            Range m_startRange

        holds the start set for the search as a Range

      - ##### m_totalEvals

            int m_totalEvals

        total number of subsets evaluated during a search

  - ### Class weka.attributeSelection.BestFirst.Link2

    class Link2 extends Object implements Serializable
    serialVersionUID:
      -8236598311516351420L

    - #### Serialized Fields

      - ##### m_data

            Object[] m_data

      - ##### m_merit

            double m_merit

  - ### Class weka.attributeSelection.BestFirst.LinkedList2

    class LinkedList2 extends ArrayList<BestFirst.Link2> implements Serializable
    serialVersionUID:
      3250538292330398929L

    - #### Serialized Fields

      - ##### m_MaxSize

            int m_MaxSize

        Max number of elements in the list

  - ### Class weka.attributeSelection.CfsSubsetEval

    class CfsSubsetEval extends ASEvaluation implements Serializable
    serialVersionUID:
      747878400813276317L

    - #### Serialized Fields

      - ##### m_c_Threshold

            double m_c_Threshold

        Threshold for admitting locally predictive features

      - ##### m_classIndex

            int m_classIndex

        The class index

      - ##### m_corr_matrix

            float[][] m_corr_matrix

        Holds the matrix of attribute correlations

      - ##### m_debug

            boolean m_debug

        Output debugging info

      - ##### m_disTransform

            Discretize m_disTransform

        Discretise attributes when class in nominal

      - ##### m_isNumeric

            boolean m_isNumeric

        Is the class numeric

      - ##### m_locallyPredictive

            boolean m_locallyPredictive

        Include locally predictive attributes

      - ##### m_missingSeparate

            boolean m_missingSeparate

        Treat missing values as separate values

      - ##### m_numAttribs

            int m_numAttribs

        Number of attributes in the training data

      - ##### m_numEntries

            int m_numEntries

        Number of entries in the correlation matrix

      - ##### m_numFilled

            AtomicInteger m_numFilled

        Number of correlations actually computed

      - ##### m_numInstances

            int m_numInstances

        Number of instances in the training data

      - ##### m_numThreads

            int m_numThreads

        The number of threads used to compute the correlation matrix. Used when correlation matrix is precomputed

      - ##### m_poolSize

            int m_poolSize

        The size of the thread pool. Usually set equal to the number of CPUs or CPU cores available

      - ##### m_preComputeCorrelationMatrix

            boolean m_preComputeCorrelationMatrix

      - ##### m_std_devs

            double[] m_std_devs

        Standard deviations of attributes (when using pearsons correlation)

      - ##### m_trainInstances

            Instances m_trainInstances

        The training instances

  - ### Class weka.attributeSelection.ClassifierAttributeEval

    class ClassifierAttributeEval extends ASEvaluation implements Serializable
    serialVersionUID:
      2442390690522602284L

    - #### Serialized Fields

      - ##### m_executionSlots

            int m_executionSlots

        The number of attributes to evaluate in parallel

      - ##### m_leaveOneOut

            boolean m_leaveOneOut

        Whether to leave each attribute out in turn and evaluate rather than just evaluate on each attribute

      - ##### m_merit

            double[] m_merit

        Holds the merit scores for each attribute

      - ##### m_trainInstances

            Instances m_trainInstances

        The training instances.

      - ##### m_wrapperSetup

            String m_wrapperSetup

        Holds toString() info for the wrapper

      - ##### m_wrapperTemplate

            WrapperSubsetEval m_wrapperTemplate

        The configured underlying Wrapper instance to use for evaluation

  - ### Class weka.attributeSelection.ClassifierSubsetEval

    class ClassifierSubsetEval extends HoldOutSubsetEvaluator implements Serializable
    serialVersionUID:
      7532217899385278710L

    - #### Serialized Fields

      - ##### m_Classifier

            Classifier m_Classifier

        Holds the classifier used when evaluating single hold-out instances - this is used by RaceSearch and the trained classifier may need to persist between calls to that particular method.

      - ##### m_ClassifierTemplate

            Classifier m_ClassifierTemplate

        holds the template classifier to use for error estimates

      - ##### m_classIndex

            int m_classIndex

        class index

      - ##### m_evaluationMeasure

            Tag m_evaluationMeasure

        The evaluation measure to use

      - ##### m_holdOutFile

            File m_holdOutFile

        the file that contains hold out/test instances

      - ##### m_holdOutInstances

            Instances m_holdOutInstances

        the instances to test on

      - ##### m_IRClassVal

            int m_IRClassVal

        If >= 0, and an IR metric is being used, then evaluate with respect to this class value (0-based index)

      - ##### m_IRClassValS

            String m_IRClassValS

        User supplied option for IR class value (either name or 1-based index)

      - ##### m_numAttribs

            int m_numAttribs

        number of attributes in the training data

      - ##### m_seed

            int m_seed

        Seed for randomizing prior to splitting training data

      - ##### m_splitPercent

            String m_splitPercent

        The split to use if doing a percentage split

      - ##### m_trainingInstances

            Instances m_trainingInstances

        training instances

      - ##### m_usePercentageSplit

            boolean m_usePercentageSplit

        Whether to hold out a percentage of the training data

      - ##### m_useTraining

            boolean m_useTraining

        evaluate on training data rather than separate hold out/test set

  - ### Class weka.attributeSelection.CorrelationAttributeEval

    class CorrelationAttributeEval extends ASEvaluation implements Serializable
    serialVersionUID:
      -4931946995055872438L

    - #### Serialized Fields

      - ##### m_correlations

            double[] m_correlations

        The correlation for each attribute

      - ##### m_detailedOutput

            boolean m_detailedOutput

        Whether to output detailed (per value) correlation for nominal attributes

      - ##### m_detailedOutputBuff

            StringBuffer m_detailedOutputBuff

        Holds the detailed output info

  - ### Class weka.attributeSelection.GainRatioAttributeEval

    class GainRatioAttributeEval extends ASEvaluation implements Serializable
    serialVersionUID:
      -8504656625598579926L

    - #### Serialized Fields

      - ##### m_classIndex

            int m_classIndex

        The class index

      - ##### m_missing_merge

            boolean m_missing_merge

        Merge missing values

      - ##### m_numClasses

            int m_numClasses

        The number of classes

      - ##### m_numInstances

            int m_numInstances

        The number of instances

      - ##### m_trainInstances

            Instances m_trainInstances

        The training instances

  - ### Class weka.attributeSelection.GreedyStepwise

    class GreedyStepwise extends ASSearch implements Serializable
    serialVersionUID:
      -6312951970168325471L

    - #### Serialized Fields

      - ##### m_ASEval

            ASEvaluation m_ASEval

      - ##### m_backward

            boolean m_backward

        Use a backwards search instead of a forwards one

      - ##### m_best_group

            BitSet m_best_group

        the best subset found

      - ##### m_bestMerit

            double m_bestMerit

        the merit of the best subset found

      - ##### m_calculatedNumToSelect

            int m_calculatedNumToSelect

      - ##### m_classIndex

            int m_classIndex

        holds the class index

      - ##### m_conservativeSelection

            boolean m_conservativeSelection

        If set then attributes will continue to be added during a forward search as long as the merit does not degrade

      - ##### m_debug

            boolean m_debug

        Print debugging output

      - ##### m_doneRanking

            boolean m_doneRanking

        used to indicate whether or not ranking has been performed

      - ##### m_doRank

            boolean m_doRank

        go from one side of the search space to the other in order to generate a ranking

      - ##### m_hasClass

            boolean m_hasClass

        does the data have a class

      - ##### m_Instances

            Instances m_Instances

      - ##### m_numAttribs

            int m_numAttribs

        number of attributes in the data

      - ##### m_numToSelect

            int m_numToSelect

        The number of attributes to select. -1 indicates that all attributes are to be retained. Has precedence over m_threshold

      - ##### m_poolSize

            int m_poolSize

      - ##### m_rankedAtts

            double[][] m_rankedAtts

        a ranked list of attribute indexes

      - ##### m_rankedSoFar

            int m_rankedSoFar

      - ##### m_rankingRequested

            boolean m_rankingRequested

        true if the user has requested a ranked list of attributes

      - ##### m_starting

            int[] m_starting

        holds an array of starting attributes

      - ##### m_startRange

            Range m_startRange

        holds the start set for the search as a Range

      - ##### m_threshold

            double m_threshold

        A threshold by which to discard attributes---used by the AttributeSelection module

  - ### Class weka.attributeSelection.HoldOutSubsetEvaluator

    class HoldOutSubsetEvaluator extends ASEvaluation implements Serializable
    serialVersionUID:
      8280529785412054174L

  - ### Class weka.attributeSelection.InfoGainAttributeEval

    class InfoGainAttributeEval extends ASEvaluation implements Serializable
    serialVersionUID:
      -1949849512589218930L

    - #### Serialized Fields

      - ##### m_Binarize

            boolean m_Binarize

        Just binarize numeric attributes

      - ##### m_InfoGains

            double[] m_InfoGains

        The info gain for each attribute

      - ##### m_missing_merge

            boolean m_missing_merge

        Treat missing values as a separate value

  - ### Class weka.attributeSelection.OneRAttributeEval

    class OneRAttributeEval extends ASEvaluation implements Serializable
    serialVersionUID:
      4386514823886856980L

    - #### Serialized Fields

      - ##### m_evalUsingTrainingData

            boolean m_evalUsingTrainingData

        Use training data to evaluate merit rather than x-val

      - ##### m_folds

            int m_folds

        Number of folds for cross validation

      - ##### m_minBucketSize

            int m_minBucketSize

        Passed on to OneR

      - ##### m_randomSeed

            int m_randomSeed

        Random number seed

      - ##### m_trainInstances

            Instances m_trainInstances

        The training instances

  - ### Class weka.attributeSelection.PrincipalComponents

    class PrincipalComponents extends UnsupervisedAttributeEvaluator implements Serializable
    serialVersionUID:
      -3675307197777734007L

    - #### Serialized Fields

      - ##### m_attributeFilter

            Remove m_attributeFilter

      - ##### m_center

            boolean m_center

        If true, center (rather than standardize) the data and compute PCA from covariance (rather than correlation) matrix.

      - ##### m_centerFilter

            Center m_centerFilter

      - ##### m_classIndex

            int m_classIndex

        Class index

      - ##### m_correlation

            no.uib.cipr.matrix.UpperSymmDenseMatrix m_correlation

        Correlation/covariance matrix for the original data

      - ##### m_coverVariance

            double m_coverVariance

        the amount of variance to cover in the original data when retaining the best n PC's

      - ##### m_eigenvalues

            double[] m_eigenvalues

        Eigenvalues for the corresponding eigenvectors

      - ##### m_eigenvectors

            double[][] m_eigenvectors

        Will hold the unordered linear transformations of the (normalized) original data

      - ##### m_eTranspose

            double[][] m_eTranspose

        holds the transposed eigenvectors for converting back to the original space

      - ##### m_hasClass

            boolean m_hasClass

        Data has a class set

      - ##### m_maxAttrsInName

            int m_maxAttrsInName

        maximum number of attributes in the transformed attribute name

      - ##### m_means

            double[] m_means

      - ##### m_nominalToBinFilter

            NominalToBinary m_nominalToBinFilter

      - ##### m_numAttribs

            int m_numAttribs

        Number of attributes

      - ##### m_numInstances

            int m_numInstances

        Number of instances

      - ##### m_originalSpaceFormat

            Instances m_originalSpaceFormat

        The header for data transformed back to the original space

      - ##### m_outputNumAtts

            int m_outputNumAtts

        The number of attributes in the pc transformed data

      - ##### m_replaceMissingFilter

            ReplaceMissingValues m_replaceMissingFilter

        Filters for original data

      - ##### m_sortedEigens

            int[] m_sortedEigens

        Sorted eigenvalues

      - ##### m_standardizeFilter

            Standardize m_standardizeFilter

      - ##### m_stdDevs

            double[] m_stdDevs

      - ##### m_sumOfEigenValues

            double m_sumOfEigenValues

        sum of the eigenvalues

      - ##### m_trainHeader

            Instances m_trainHeader

        Keep a copy for the class attribute (if set)

      - ##### m_trainInstances

            Instances m_trainInstances

        The data to transform analyse/transform

      - ##### m_transBackToOriginal

            boolean m_transBackToOriginal

        transform the data through the pc space and back to the original space ?

      - ##### m_transformedFormat

            Instances m_transformedFormat

        The header for the transformed data format

  - ### Class weka.attributeSelection.Ranker

    class Ranker extends ASSearch implements Serializable
    serialVersionUID:
      -9086714848510751934L

    - #### Serialized Fields

      - ##### m_attributeList

            int[] m_attributeList

        Holds the ordered list of attributes

      - ##### m_attributeMerit

            double[] m_attributeMerit

        Holds the list of attribute merit scores

      - ##### m_calculatedNumToSelect

            int m_calculatedNumToSelect

        Used to compute the number to select

      - ##### m_classIndex

            int m_classIndex

        Class index of the data if supervised evaluator

      - ##### m_hasClass

            boolean m_hasClass

        Data has class attribute---if unsupervised evaluator then no class

      - ##### m_numAttribs

            int m_numAttribs

        The number of attribtes

      - ##### m_numToSelect

            int m_numToSelect

        The number of attributes to select. -1 indicates that all attributes are to be retained. Has precedence over m_threshold

      - ##### m_starting

            int[] m_starting

        Holds the starting set as an array of attributes

      - ##### m_startRange

            Range m_startRange

        Holds the start set for the search as a range

      - ##### m_threshold

            double m_threshold

        A threshold by which to discard attributes---used by the AttributeSelection module

  - ### Class weka.attributeSelection.ReliefFAttributeEval

    class ReliefFAttributeEval extends ASEvaluation implements Serializable
    serialVersionUID:
      -8422186665795839379L

    - #### Serialized Fields

      - ##### m_classIndex

            int m_classIndex

        The class index

      - ##### m_classProbs

            double[] m_classProbs

        Prior class probabilities (discrete class case)

      - ##### m_index

            int[] m_index

        Index in the m_karray of the farthest instance for each class

      - ##### m_karray

            double[][][] m_karray

        k nearest scores + instance indexes for n classes

      - ##### m_Knn

            int m_Knn

        The number of nearest hits/misses

      - ##### m_maxArray

            double[] m_maxArray

        Upper bound for numeric attributes

      - ##### m_minArray

            double[] m_minArray

        Lower bound for numeric attributes

      - ##### m_nda

            double[] m_nda

        Used to hold the prob of different value of an attribute given nearest instances (numeric class case)

      - ##### m_ndc

            double m_ndc

        Used to hold the probability of a different class val given nearest instances (numeric class)

      - ##### m_ndcda

            double[] m_ndcda

        Used to hold the prob of a different class val and different att val given nearest instances (numeric class case)

      - ##### m_numAttribs

            int m_numAttribs

        The number of attributes

      - ##### m_numClasses

            int m_numClasses

        The number of classes if class is nominal

      - ##### m_numericClass

            boolean m_numericClass

        Numeric class

      - ##### m_numInstances

            int m_numInstances

        The number of instances

      - ##### m_sampleM

            int m_sampleM

        The number of instances to sample when estimating attributes default == -1, use all instances

      - ##### m_seed

            int m_seed

        Random number seed used for sampling instances

      - ##### m_sigma

            int m_sigma

      - ##### m_stored

            int[] m_stored

        Number of nearest neighbours stored of each class

      - ##### m_trainInstances

            Instances m_trainInstances

        The training instances

      - ##### m_weightByDistance

            boolean m_weightByDistance

        Weight by distance rather than equal weights

      - ##### m_weights

            double[] m_weights

        Holds the weights that relief assigns to attributes

      - ##### m_weightsByRank

            double[] m_weightsByRank

        used to (optionally) weight nearest neighbours by their distance from the instance in question. Each entry holds exp(-((rank(r_i, i_j)/sigma)^2)) where rank(r_i,i_j) is the rank of instance i_j in a sequence of instances ordered by the distance from r_i. sigma is a user defined parameter, default=20

      - ##### m_worst

            double[] m_worst

        Keep track of the farthest instance for each class

  - ### Class weka.attributeSelection.SymmetricalUncertAttributeEval

    class SymmetricalUncertAttributeEval extends ASEvaluation implements Serializable
    serialVersionUID:
      -8096505776132296416L

    - #### Serialized Fields

      - ##### m_classIndex

            int m_classIndex

        The class index

      - ##### m_missing_merge

            boolean m_missing_merge

        Treat missing values as a separate value

      - ##### m_numClasses

            int m_numClasses

        The number of classes

      - ##### m_numInstances

            int m_numInstances

        The number of instances

      - ##### m_trainInstances

            Instances m_trainInstances

        The training instances

  - ### Class weka.attributeSelection.UnsupervisedAttributeEvaluator

    class UnsupervisedAttributeEvaluator extends ASEvaluation implements Serializable
    serialVersionUID:
      -4100897318675336178L

  - ### Class weka.attributeSelection.UnsupervisedSubsetEvaluator

    class UnsupervisedSubsetEvaluator extends ASEvaluation implements Serializable
    serialVersionUID:
      627934376267488763L

  - ### Class weka.attributeSelection.WrapperSubsetEval

    class WrapperSubsetEval extends ASEvaluation implements Serializable
    serialVersionUID:
      -4573057658746728675L

    - #### Serialized Fields

      - ##### m_BaseClassifier

            Classifier m_BaseClassifier

        holds the base classifier object

      - ##### m_classIndex

            int m_classIndex

        class index

      - ##### m_Evaluation

            Evaluation m_Evaluation

        holds an evaluation object

      - ##### m_evaluationMeasure

            Tag m_evaluationMeasure

        The evaluation measure to use

      - ##### m_folds

            int m_folds

        number of folds to use for cross validation

      - ##### m_IRClassVal

            int m_IRClassVal

        If >= 0, and an IR metric is being used, then evaluate with respect to this class value (0-based index)

      - ##### m_IRClassValS

            String m_IRClassValS

        User supplied option for IR class value (either name or 1-based index)

      - ##### m_numAttribs

            int m_numAttribs

        number of attributes in the training data

      - ##### m_seed

            int m_seed

        random number seed

      - ##### m_threshold

            double m_threshold

        the threshold by which to do further cross validations when estimating the accuracy of a subset

      - ##### m_trainInstances

            Instances m_trainInstances

        training instances

  - ### Class weka.attributeSelection.WrapperSubsetEval.PluginTag

    class PluginTag extends Tag implements Serializable
    serialVersionUID:
      -6978438858413428382L

    - #### Serialized Fields

      - ##### m_metric

            AbstractEvaluationMetric m_metric

        The metric object itself

      - ##### m_statisticName

            String m_statisticName

        The particular statistic from the metric that this tag pertains to

- ## Package weka.classifiers

  - ### Class weka.classifiers.AbstractClassifier

    class AbstractClassifier extends Object implements Serializable
    serialVersionUID:
      6502780192411755341L

    - #### Serialized Fields

      - ##### m_BatchSize

            String m_BatchSize

      - ##### m_Debug

            boolean m_Debug

        Whether the classifier is run in debug mode.

      - ##### m_DoNotCheckCapabilities

            boolean m_DoNotCheckCapabilities

        Whether capabilities should not be checked before classifier is built.

      - ##### m_numDecimalPlaces

            int m_numDecimalPlaces

  - ### Class weka.classifiers.AggregateableEvaluation

    class AggregateableEvaluation extends Evaluation implements Serializable
    serialVersionUID:
      6850546230173753210L

  - ### Class weka.classifiers.CostMatrix

    class CostMatrix extends Object implements Serializable
    serialVersionUID:
      -1973792250544554965L

    - #### Serialized Fields

      - ##### m_matrix

            Object[][] m_matrix

        [rows][columns]

      - ##### m_size

            int m_size

  - ### Class weka.classifiers.Evaluation

    class Evaluation extends Object implements Serializable
    serialVersionUID:
      -170766452472965668L

    - #### Serialized Fields

      - ##### m_delegate

            Evaluation m_delegate

        The actual evaluation object that we delegate to

  - ### Class weka.classifiers.IteratedSingleClassifierEnhancer

    class IteratedSingleClassifierEnhancer extends SingleClassifierEnhancer implements Serializable
    serialVersionUID:
      -6217979135443319724L

    - #### Serialized Fields

      - ##### m_Classifiers

            Classifier[] m_Classifiers

        Array for storing the generated base classifiers.

      - ##### m_NumIterations

            int m_NumIterations

        The number of iterations.

  - ### Class weka.classifiers.MultipleClassifiersCombiner

    class MultipleClassifiersCombiner extends AbstractClassifier implements Serializable
    serialVersionUID:
      2776436621129422119L

    - #### Serialized Fields

      - ##### m_Classifiers

            Classifier[] m_Classifiers

        Array for storing the generated base classifiers.

  - ### Class weka.classifiers.ParallelIteratedSingleClassifierEnhancer

    class ParallelIteratedSingleClassifierEnhancer extends IteratedSingleClassifierEnhancer implements Serializable
    serialVersionUID:
      -5026378741833046436L

    - #### Serialized Fields

      - ##### m_numExecutionSlots

            int m_numExecutionSlots

        The number of threads to have executing at any one time

  - ### Class weka.classifiers.ParallelMultipleClassifiersCombiner

    class ParallelMultipleClassifiersCombiner extends MultipleClassifiersCombiner implements Serializable
    serialVersionUID:
      728109028953726626L

    - #### Serialized Fields

      - ##### m_completed

            int m_completed

        The number of classifiers completed so far

      - ##### m_failed

            int m_failed

        The number of classifiers that experienced a failure of some sort during construction

      - ##### m_numExecutionSlots

            int m_numExecutionSlots

        The number of threads to have executing at any one time

  - ### Class weka.classifiers.RandomizableClassifier

    class RandomizableClassifier extends AbstractClassifier implements Serializable
    serialVersionUID:
      -8816375798262351903L

    - #### Serialized Fields

      - ##### m_Seed

            int m_Seed

        The random number seed.

  - ### Class weka.classifiers.RandomizableIteratedSingleClassifierEnhancer

    class RandomizableIteratedSingleClassifierEnhancer extends IteratedSingleClassifierEnhancer implements Serializable
    serialVersionUID:
      5063351391524938557L

    - #### Serialized Fields

      - ##### m_Seed

            int m_Seed

        The random number seed.

  - ### Class weka.classifiers.RandomizableMultipleClassifiersCombiner

    class RandomizableMultipleClassifiersCombiner extends MultipleClassifiersCombiner implements Serializable
    serialVersionUID:
      5057936555724785679L

    - #### Serialized Fields

      - ##### m_Seed

            int m_Seed

        The random number seed.

  - ### Class weka.classifiers.RandomizableParallelIteratedSingleClassifierEnhancer

    class RandomizableParallelIteratedSingleClassifierEnhancer extends ParallelIteratedSingleClassifierEnhancer implements Serializable
    serialVersionUID:
      1298141000373615374L

    - #### Serialized Fields

      - ##### m_Seed

            int m_Seed

        The random number seed.

  - ### Class weka.classifiers.RandomizableParallelMultipleClassifiersCombiner

    class RandomizableParallelMultipleClassifiersCombiner extends ParallelMultipleClassifiersCombiner implements Serializable
    serialVersionUID:
      8274061943448676943L

    - #### Serialized Fields

      - ##### m_Seed

            int m_Seed

        The random number seed.

  - ### Class weka.classifiers.RandomizableSingleClassifierEnhancer

    class RandomizableSingleClassifierEnhancer extends SingleClassifierEnhancer implements Serializable
    serialVersionUID:
      558286687096157160L

    - #### Serialized Fields

      - ##### m_Seed

            int m_Seed

        The random number seed.

  - ### Class weka.classifiers.SingleClassifierEnhancer

    class SingleClassifierEnhancer extends AbstractClassifier implements Serializable
    serialVersionUID:
      -3665885256363525164L

    - #### Serialized Fields

      - ##### m_Classifier

            Classifier m_Classifier

        The base classifier to use

- ## Package weka.classifiers.bayes

  - ### Class weka.classifiers.bayes.BayesNet

    class BayesNet extends AbstractClassifier implements Serializable
    serialVersionUID:
      746037443258775954L

    - #### Serialized Fields

      - ##### m_ADTree

            ADNode m_ADTree

        Datastructure containing ADTree representation of the database. This may result in more efficient access to the data.

      - ##### m_BayesNetEstimator

            BayesNetEstimator m_BayesNetEstimator

        Search algorithm used for learning the structure of a network.

      - ##### m_bUseADTree

            boolean m_bUseADTree

        Use the experimental ADTree datastructure for calculating contingency tables

      - ##### m_DiscretizeFilter

            Discretize m_DiscretizeFilter

        filter used to quantize continuous variables, if any

      - ##### m_Distributions

            Estimator[][] m_Distributions

        The attribute estimators containing CPTs.

      - ##### m_Instances

            Instances m_Instances

        The dataset header for the purposes of printing out a semi-intelligible model

      - ##### m_MissingValuesFilter

            ReplaceMissingValues m_MissingValuesFilter

        filter used to fill in missing values, if any

      - ##### m_nNonDiscreteAttribute

            int m_nNonDiscreteAttribute

        attribute index of a non-nominal attribute

      - ##### m_NumClasses

            int m_NumClasses

        The number of classes

      - ##### m_NumInstances

            int m_NumInstances

        The number of instances the model was built from

      - ##### m_otherBayesNet

            BIFReader m_otherBayesNet

        Bayes network to compare the structure with.

      - ##### m_ParentSets

            ParentSet[] m_ParentSets

        The parent sets.

      - ##### m_SearchAlgorithm

            SearchAlgorithm m_SearchAlgorithm

        Search algorithm used for learning the structure of a network.

  - ### Class weka.classifiers.bayes.NaiveBayes

    class NaiveBayes extends AbstractClassifier implements Serializable
    serialVersionUID:
      5995231201785697655L

    - #### Serialized Fields

      - ##### m_ClassDistribution

            Estimator m_ClassDistribution

        The class estimator.

      - ##### m_Disc

            Discretize m_Disc

        The discretization filter.

      - ##### m_displayModelInOldFormat

            boolean m_displayModelInOldFormat

      - ##### m_Distributions

            Estimator[][] m_Distributions

        The attribute estimators.

      - ##### m_Instances

            Instances m_Instances

        The dataset header for the purposes of printing out a semi-intelligible model

      - ##### m_NumClasses

            int m_NumClasses

        The number of classes (or 1 for numeric class)

      - ##### m_UseDiscretization

            boolean m_UseDiscretization

        Whether to use discretization than normal distribution for numeric attributes

      - ##### m_UseKernelEstimator

            boolean m_UseKernelEstimator

        Whether to use kernel density estimator rather than normal distribution for numeric attributes

  - ### Class weka.classifiers.bayes.NaiveBayesMultinomial

    class NaiveBayesMultinomial extends AbstractClassifier implements Serializable
    serialVersionUID:
      5932177440181257085L

    - #### Serialized Fields

      - ##### m_headerInfo

            Instances m_headerInfo

        copy of header information for use in toString method

      - ##### m_numAttributes

            int m_numAttributes

        number of unique words

      - ##### m_numClasses

            int m_numClasses

        number of class values

      - ##### m_probOfClass

            double[] m_probOfClass

        the probability of a class (i.e. Pr[H]).

      - ##### m_probOfWordGivenClass

            double[][] m_probOfWordGivenClass

        probability that a word (w) exists in a class (H) (i.e. Pr[w|H]) The matrix is in the this format: probOfWordGivenClass[class][wordAttribute] NOTE: the values are actually the log of Pr[w|H]

  - ### Class weka.classifiers.bayes.NaiveBayesMultinomialText

    class NaiveBayesMultinomialText extends AbstractClassifier implements Serializable
    serialVersionUID:
      2139025532014821394L

    - #### Serialized Fields

      - ##### m_data

            Instances m_data

        The header of the training data

      - ##### m_leplace

            double m_leplace

        Leplace-like correction factor for zero frequency

      - ##### m_lnorm

            double m_lnorm

        The L-norm to use

      - ##### m_lowercaseTokens

            boolean m_lowercaseTokens

        Whether or not to convert all tokens to lowercase

      - ##### m_minWordP

            double m_minWordP

        Only consider dictionary words (features) that occur at least this many times

      - ##### m_norm

            double m_norm

        The length that each document vector should have in the end

      - ##### m_normalize

            boolean m_normalize

        normailize document length ?

      - ##### m_numModels

            int m_numModels

      - ##### m_periodicP

            int m_periodicP

        The number of training instances at which to periodically prune the dictionary of min frequency words. Empty or null string indicates don't prune

      - ##### m_probOfClass

            double[] m_probOfClass

      - ##### m_probOfWordGivenClass

            Map<Integer,LinkedHashMap<String,weka.classifiers.bayes.NaiveBayesMultinomialText.Count>> m_probOfWordGivenClass

      - ##### m_stemmer

            Stemmer m_stemmer

        The stemming algorithm.

      - ##### m_StopwordsHandler

            StopwordsHandler m_StopwordsHandler

        Stopword handler to use.

      - ##### m_t

            double m_t

        Holds the current instance number

      - ##### m_tokenizer

            Tokenizer m_tokenizer

        The tokenizer to use

      - ##### m_wordFrequencies

            boolean m_wordFrequencies

        Use word frequencies rather than bag-of-words if true

      - ##### m_wordsPerClass

            double[] m_wordsPerClass

  - ### Class weka.classifiers.bayes.NaiveBayesMultinomialUpdateable

    class NaiveBayesMultinomialUpdateable extends NaiveBayesMultinomial implements Serializable
    serialVersionUID:
      -7204398796974263186L

    - #### Serialized Fields

      - ##### m_wordsPerClass

            double[] m_wordsPerClass

        the number of words per class.

  - ### Class weka.classifiers.bayes.NaiveBayesUpdateable

    class NaiveBayesUpdateable extends NaiveBayes implements Serializable
    serialVersionUID:
      -5354015843807192221L

- ## Package weka.classifiers.bayes.net

  - ### Class weka.classifiers.bayes.net.ADNode

    class ADNode extends Object implements Serializable
    serialVersionUID:
      397409728366910204L

    - #### Serialized Fields

      - ##### m_Instances

            Instance[] m_Instances

        list of Instance children (either m_Instances or m_VaryNodes is instantiated)

      - ##### m_nCount

            int m_nCount

        count

      - ##### m_nStartNode

            int m_nStartNode

        first node in VaryNode array

      - ##### m_VaryNodes

            VaryNode[] m_VaryNodes

        list of VaryNode children

  - ### Class weka.classifiers.bayes.net.BayesNetGenerator

    class BayesNetGenerator extends EditableBayesNet implements Serializable
    serialVersionUID:
      -7462571170596157720L

    - #### Serialized Fields

      - ##### m_bGenerateNet

            boolean m_bGenerateNet

      - ##### m_nCardinality

            int m_nCardinality

      - ##### m_nNrOfArcs

            int m_nNrOfArcs

      - ##### m_nNrOfInstances

            int m_nNrOfInstances

      - ##### m_nNrOfNodes

            int m_nNrOfNodes

      - ##### m_nSeed

            int m_nSeed

        the seed value

      - ##### m_sBIFFile

            String m_sBIFFile

      - ##### random

            Random random

        the random number generator

  - ### Class weka.classifiers.bayes.net.BIFReader

    class BIFReader extends BayesNet implements Serializable
    serialVersionUID:
      -8358864680379881429L

    - #### Serialized Fields

      - ##### m_nPositionX

            int[] m_nPositionX

      - ##### m_nPositionY

            int[] m_nPositionY

      - ##### m_order

            int[] m_order

      - ##### m_sFile

            String m_sFile

        the current filename

  - ### Class weka.classifiers.bayes.net.EditableBayesNet

    class EditableBayesNet extends BayesNet implements Serializable
    serialVersionUID:
      746037443258735954L

    - #### Serialized Fields

      - ##### m_bNeedsUndoAction

            boolean m_bNeedsUndoAction

        flag to indicate whether an edit action needs to introduce an undo action. This is only false when an undo or redo action is performed.

      - ##### m_fMarginP

            ArrayList<double[]> m_fMarginP

        marginal distributions *

      - ##### m_nCurrentEditAction

            int m_nCurrentEditAction

        current action in undo stack

      - ##### m_nEvidence

            ArrayList<Integer> m_nEvidence

        evidence values, used for evidence propagation *

      - ##### m_nPositionX

            ArrayList<Integer> m_nPositionX

        location of nodes, used for graph drawing *

      - ##### m_nPositionY

            ArrayList<Integer> m_nPositionY

      - ##### m_nSavedPointer

            int m_nSavedPointer

        action that the network is saved

      - ##### m_undoStack

            ArrayList<weka.classifiers.bayes.net.EditableBayesNet.UndoAction> m_undoStack

        undo stack for undoin edit actions, or redo edit actions

  - ### Class weka.classifiers.bayes.net.GUI

    class GUI extends JPanel implements Serializable
    serialVersionUID:
      -2038911085935515624L

    - #### Serialized Fields

      - ##### a_about

            Action a_about

      - ##### a_addarc

            Action a_addarc

      - ##### a_addnode

            weka.classifiers.bayes.net.GUI.ActionAddNode a_addnode

      - ##### a_alignbottom

            Action a_alignbottom

      - ##### a_alignleft

            Action a_alignleft

      - ##### a_alignright

            Action a_alignright

      - ##### a_aligntop

            Action a_aligntop

      - ##### a_centerhorizontal

            Action a_centerhorizontal

      - ##### a_centervertical

            Action a_centervertical

      - ##### a_copynode

            Action a_copynode

      - ##### a_cutnode

            Action a_cutnode

      - ##### a_datagenerator

            Action a_datagenerator

      - ##### a_datasetter

            Action a_datasetter

      - ##### a_delarc

            Action a_delarc

      - ##### a_delnode

            Action a_delnode

      - ##### a_export

            weka.classifiers.bayes.net.GUI.ActionExport a_export

      - ##### a_help

            Action a_help

      - ##### a_layout

            Action a_layout

      - ##### a_learn

            Action a_learn

      - ##### a_learnCPT

            Action a_learnCPT

      - ##### a_load

            Action a_load

      - ##### a_networkgenerator

            Action a_networkgenerator

      - ##### a_new

            Action a_new

        actions triggered by GUI events

      - ##### a_pastenode

            Action a_pastenode

      - ##### a_print

            weka.classifiers.bayes.net.GUI.ActionPrint a_print

      - ##### a_quit

            Action a_quit

      - ##### a_redo

            Action a_redo

      - ##### a_save

            Action a_save

      - ##### a_saveas

            Action a_saveas

      - ##### a_selectall

            Action a_selectall

      - ##### a_spacehorizontal

            Action a_spacehorizontal

      - ##### a_spacevertical

            Action a_spacevertical

      - ##### a_undo

            Action a_undo

      - ##### a_viewstatusbar

            Action a_viewstatusbar

      - ##### a_viewtoolbar

            Action a_viewtoolbar

      - ##### a_zoomin

            Action a_zoomin

      - ##### a_zoomout

            Action a_zoomout

      - ##### ICONPATH

            String ICONPATH

        path for icons

      - ##### m_BayesNet

            EditableBayesNet m_BayesNet

        Container of Bayesian network

      - ##### m_bViewCliques

            boolean m_bViewCliques

      - ##### m_bViewMargins

            boolean m_bViewMargins

        flag indicating whether marginal distributions of each of the nodes should be shown in display.

      - ##### m_clipboard

            weka.classifiers.bayes.net.GUI.ClipBoard m_clipboard

      - ##### m_fScale

            double m_fScale

        current zoom value

      - ##### m_GraphPanel

            weka.classifiers.bayes.net.GUI.GraphPanel m_GraphPanel

        Panel actually displaying the graph

      - ##### m_Instances

            Instances m_Instances

        data selected from file. Used to train a Bayesian network on

      - ##### m_jScrollPane

            JScrollPane m_jScrollPane

        this contains the m_GraphPanel GraphPanel

      - ##### m_jStatusBar

            JLabel m_jStatusBar

        status bar at bottom of window

      - ##### m_jTbTools

            JToolBar m_jTbTools

        toolbar containing buttons at top of window

      - ##### m_jTfNodeHeight

            JTextField m_jTfNodeHeight

        TextField for nodes height

      - ##### m_jTfNodeWidth

            JTextField m_jTfNodeWidth

        TextField for node's width

      - ##### m_jTfZoom

            JTextField m_jTfZoom

        Text field for specifying zoom

      - ##### m_layoutEngine

            LayoutEngine m_layoutEngine

        The current LayoutEngine

      - ##### m_marginCalculator

            MarginCalculator m_marginCalculator

        used for calculating marginals in Bayesian netwowrks

      - ##### m_marginCalculatorWithEvidence

            MarginCalculator m_marginCalculatorWithEvidence

        used for calculating marginals in Bayesian netwowrks when evidence is present

      - ##### m_menuBar

            JMenuBar m_menuBar

        The menu bar

      - ##### m_nCurrentNode

            int m_nCurrentNode

        node currently selected through right clicking

      - ##### m_nNodeHeight

            int m_nNodeHeight

        standard width of node

      - ##### m_nNodeWidth

            int m_nNodeWidth

      - ##### m_nPaddedNodeWidth

            int m_nPaddedNodeWidth

      - ##### m_nSelectedRect

            Rectangle m_nSelectedRect

        selection rectangle drawn through dragging with left mouse button

      - ##### m_nZoomPercents

            int[] m_nZoomPercents

        used when using zoomIn and zoomOut buttons

      - ##### m_Selection

            weka.classifiers.bayes.net.GUI.Selection m_Selection

        selection of nodes

      - ##### m_sFileName

            String m_sFileName

        String containing file name storing current network

  - ### Class weka.classifiers.bayes.net.MarginCalculator

    class MarginCalculator extends Object implements Serializable
    serialVersionUID:
      650278019241175534L

    - #### Serialized Fields

      - ##### jtNodes

            MarginCalculator.JunctionTreeNode[] jtNodes

      - ##### m_debug

            boolean m_debug

      - ##### m_Margins

            double[][] m_Margins

      - ##### m_root

            MarginCalculator.JunctionTreeNode m_root

  - ### Class weka.classifiers.bayes.net.MarginCalculator.JunctionTreeNode

    class JunctionTreeNode extends Object implements Serializable
    serialVersionUID:
      650278019241175536L

    - #### Serialized Fields

      - ##### m_bayesNet

            BayesNet m_bayesNet

        reference Bayes net for information about variables like name, cardinality, etc. but not for relations between nodes

      - ##### m_children

            Vector<MarginCalculator.JunctionTreeNode> m_children

      - ##### m_fi

            double[] m_fi

        potentials for first network

      - ##### m_MarginalP

            double[][] m_MarginalP

      - ##### m_nCardinality

            int m_nCardinality

        cardinality of the instances of variables in this junction node

      - ##### m_nNodes

            int[] m_nNodes

        nodes of the Bayes net in this junction node

      - ##### m_P

            double[] m_P

        distribution over this junction node according to first Bayes network

      - ##### m_parentSeparator

            MarginCalculator.JunctionTreeSeparator m_parentSeparator

  - ### Class weka.classifiers.bayes.net.MarginCalculator.JunctionTreeSeparator

    class JunctionTreeSeparator extends Object implements Serializable
    serialVersionUID:
      6502780192411755343L

    - #### Serialized Fields

      - ##### m_bayesNet

            BayesNet m_bayesNet

      - ##### m_childNode

            MarginCalculator.JunctionTreeNode m_childNode

      - ##### m_fiChild

            double[] m_fiChild

      - ##### m_fiParent

            double[] m_fiParent

      - ##### m_nCardinality

            int m_nCardinality

      - ##### m_nNodes

            int[] m_nNodes

      - ##### m_parentNode

            MarginCalculator.JunctionTreeNode m_parentNode

  - ### Class weka.classifiers.bayes.net.ParentSet

    class ParentSet extends Object implements Serializable
    serialVersionUID:
      4155021284407181838L

    - #### Serialized Fields

      - ##### m_nCardinalityOfParents

            int m_nCardinalityOfParents

        Holds cardinality of parents (= number of instantiations the parents can take)

      - ##### m_nNrOfParents

            int m_nNrOfParents

        Holds number of parents

      - ##### m_nParents

            int[] m_nParents

        Holds indexes of parents

  - ### Class weka.classifiers.bayes.net.VaryNode

    class VaryNode extends Object implements Serializable
    serialVersionUID:
      -6196294370675872424L

    - #### Serialized Fields

      - ##### m_ADNodes

            ADNode[] m_ADNodes

        list of ADNode children

      - ##### m_iNode

            int m_iNode

        index of the node varied

      - ##### m_nMCV

            int m_nMCV

        most common value

- ## Package weka.classifiers.bayes.net.estimate

  - ### Class weka.classifiers.bayes.net.estimate.BayesNetEstimator

    class BayesNetEstimator extends Object implements Serializable
    serialVersionUID:
      2184330197666253884L

    - #### Serialized Fields

      - ##### m_fAlpha

            double m_fAlpha

        Holds prior on count

  - ### Class weka.classifiers.bayes.net.estimate.BMAEstimator

    class BMAEstimator extends SimpleEstimator implements Serializable
    serialVersionUID:
      -1846028304233257309L

    - #### Serialized Fields

      - ##### m_bUseK2Prior

            boolean m_bUseK2Prior

        whether to use K2 prior

  - ### Class weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes

    class DiscreteEstimatorBayes extends Estimator implements Serializable
    serialVersionUID:
      4215400230843212684L

    - #### Serialized Fields

      - ##### m_Counts

            double[] m_Counts

        Hold the counts

      - ##### m_fPrior

            double m_fPrior

        Holds the prior probability

      - ##### m_nSymbols

            int m_nSymbols

        Holds number of symbols in distribution

      - ##### m_SumOfCounts

            double m_SumOfCounts

        Hold the sum of counts

  - ### Class weka.classifiers.bayes.net.estimate.DiscreteEstimatorFullBayes

    class DiscreteEstimatorFullBayes extends DiscreteEstimatorBayes implements Serializable
    serialVersionUID:
      6774941981423312133L

  - ### Class weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator

    class MultiNomialBMAEstimator extends BayesNetEstimator implements Serializable
    serialVersionUID:
      8330705772601586313L

    - #### Serialized Fields

      - ##### m_bUseK2Prior

            boolean m_bUseK2Prior

        whether to use K2 prior

  - ### Class weka.classifiers.bayes.net.estimate.SimpleEstimator

    class SimpleEstimator extends BayesNetEstimator implements Serializable
    serialVersionUID:
      5874941612331806172L

- ## Package weka.classifiers.bayes.net.search

  - ### Class weka.classifiers.bayes.net.search.SearchAlgorithm

    class SearchAlgorithm extends Object implements Serializable
    serialVersionUID:
      6164792240778525312L

    - #### Serialized Fields

      - ##### m_bInitAsNaiveBayes

            boolean m_bInitAsNaiveBayes

        determines whether initial structure is an empty graph or a Naive Bayes network

      - ##### m_bMarkovBlanketClassifier

            boolean m_bMarkovBlanketClassifier

        Determines whether after structure is found a MarkovBlanketClassifier correction should be applied If this is true, m_bInitAsNaiveBayes is overridden and interpreted as false.

      - ##### m_nMaxNrOfParents

            int m_nMaxNrOfParents

        Holds upper bound on number of parents

      - ##### m_sInitalBIFFile

            String m_sInitalBIFFile

        File name containing initial network structure. This can be used as starting point for structure search It will be ignored if not speficied. When specified, it overrides the InitAsNaivBayes flag.

- ## Package weka.classifiers.bayes.net.search.ci

  - ### Class weka.classifiers.bayes.net.search.ci.CISearchAlgorithm

    class CISearchAlgorithm extends LocalScoreSearchAlgorithm implements Serializable
    serialVersionUID:
      3165802334119704560L

    - #### Serialized Fields

      - ##### m_BayesNet

            BayesNet m_BayesNet

      - ##### m_instances

            Instances m_instances

  - ### Class weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm

    class ICSSearchAlgorithm extends CISearchAlgorithm implements Serializable
    serialVersionUID:
      -2510985917284798576L

    - #### Serialized Fields

      - ##### m_nMaxCardinality

            int m_nMaxCardinality

        maximum size of separating set

- ## Package weka.classifiers.bayes.net.search.fixed

  - ### Class weka.classifiers.bayes.net.search.fixed.FromFile

    class FromFile extends SearchAlgorithm implements Serializable
    serialVersionUID:
      7334358169507619525L

    - #### Serialized Fields

      - ##### m_sBIFFile

            String m_sBIFFile

        name of file to read structure from

  - ### Class weka.classifiers.bayes.net.search.fixed.NaiveBayes

    class NaiveBayes extends SearchAlgorithm implements Serializable
    serialVersionUID:
      -4808572519709755811L

- ## Package weka.classifiers.bayes.net.search.global

  - ### Class weka.classifiers.bayes.net.search.global.GeneticSearch

    class GeneticSearch extends GlobalScoreSearchAlgorithm implements Serializable
    serialVersionUID:
      4236165533882462203L

    - #### Serialized Fields

      - ##### g_bIsSquare

            boolean[] g_bIsSquare

        used in BayesNetRepresentation for efficiently determining whether a number is square

      - ##### m_bUseCrossOver

            boolean m_bUseCrossOver

        use cross-over?

      - ##### m_bUseMutation

            boolean m_bUseMutation

        use mutation?

      - ##### m_bUseTournamentSelection

            boolean m_bUseTournamentSelection

        use tournament selection or take best sub-population

      - ##### m_nDescendantPopulationSize

            int m_nDescendantPopulationSize

        size of descendant population

      - ##### m_nPopulationSize

            int m_nPopulationSize

        size of population

      - ##### m_nRuns

            int m_nRuns

        number of runs

      - ##### m_nSeed

            int m_nSeed

        random number seed

      - ##### m_random

            Random m_random

        random number generator

  - ### Class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm

    class GlobalScoreSearchAlgorithm extends SearchAlgorithm implements Serializable
    serialVersionUID:
      7341389867906199781L

    - #### Serialized Fields

      - ##### m_BayesNet

            BayesNet m_BayesNet

        points to Bayes network for which a structure is searched for

      - ##### m_bUseProb

            boolean m_bUseProb

        toggle between scoring using accuracy = 0-1 loss (when false) or class probabilities (when true)

      - ##### m_nCVType

            int m_nCVType

        Holds the cross validation strategy used to measure quality of network

      - ##### m_nNrOfFolds

            int m_nNrOfFolds

        number of folds for k-fold cross validation

  - ### Class weka.classifiers.bayes.net.search.global.HillClimber

    class HillClimber extends GlobalScoreSearchAlgorithm implements Serializable
    serialVersionUID:
      -3885042888195820149L

    - #### Serialized Fields

      - ##### m_bUseArcReversal

            boolean m_bUseArcReversal

        use the arc reversal operator

  - ### Class weka.classifiers.bayes.net.search.global.K2

    class K2 extends GlobalScoreSearchAlgorithm implements Serializable
    serialVersionUID:
      -6626871067466338256L

    - #### Serialized Fields

      - ##### m_bRandomOrder

            boolean m_bRandomOrder

        Holds flag to indicate ordering should be random

  - ### Class weka.classifiers.bayes.net.search.global.RepeatedHillClimber

    class RepeatedHillClimber extends HillClimber implements Serializable
    serialVersionUID:
      -7359197180460703069L

    - #### Serialized Fields

      - ##### m_nRuns

            int m_nRuns

        number of runs

      - ##### m_nSeed

            int m_nSeed

        random number seed

      - ##### m_random

            Random m_random

        random number generator

  - ### Class weka.classifiers.bayes.net.search.global.SimulatedAnnealing

    class SimulatedAnnealing extends GlobalScoreSearchAlgorithm implements Serializable
    serialVersionUID:
      -5482721887881010916L

    - #### Serialized Fields

      - ##### m_bUseArcReversal

            boolean m_bUseArcReversal

        use the arc reversal operator

      - ##### m_fDelta

            double m_fDelta

        change in temperature at every run

      - ##### m_fTStart

            double m_fTStart

        start temperature

      - ##### m_nRuns

            int m_nRuns

        number of runs

      - ##### m_nSeed

            int m_nSeed

        random number seed

      - ##### m_random

            Random m_random

        random number generator

  - ### Class weka.classifiers.bayes.net.search.global.TabuSearch

    class TabuSearch extends HillClimber implements Serializable
    serialVersionUID:
      1176705618756672292L

    - #### Serialized Fields

      - ##### m_nRuns

            int m_nRuns

        number of runs

      - ##### m_nTabuList

            int m_nTabuList

        size of tabu list

      - ##### m_oTabuList

            weka.classifiers.bayes.net.search.global.HillClimber.Operation[] m_oTabuList

        the actual tabu list

  - ### Class weka.classifiers.bayes.net.search.global.TAN

    class TAN extends GlobalScoreSearchAlgorithm implements Serializable
    serialVersionUID:
      1715277053980895298L

- ## Package weka.classifiers.bayes.net.search.local

  - ### Class weka.classifiers.bayes.net.search.local.GeneticSearch

    class GeneticSearch extends LocalScoreSearchAlgorithm implements Serializable
    serialVersionUID:
      -7037070678911459757L

    - #### Serialized Fields

      - ##### g_bIsSquare

            boolean[] g_bIsSquare

        used in BayesNetRepresentation for efficiently determining whether a number is square

      - ##### m_bUseCrossOver

            boolean m_bUseCrossOver

        use cross-over?

      - ##### m_bUseMutation

            boolean m_bUseMutation

        use mutation?

      - ##### m_bUseTournamentSelection

            boolean m_bUseTournamentSelection

        use tournament selection or take best sub-population

      - ##### m_nDescendantPopulationSize

            int m_nDescendantPopulationSize

        size of descendant population

      - ##### m_nPopulationSize

            int m_nPopulationSize

        size of population

      - ##### m_nRuns

            int m_nRuns

        number of runs

      - ##### m_nSeed

            int m_nSeed

        random number seed

      - ##### m_random

            Random m_random

        random number generator

  - ### Class weka.classifiers.bayes.net.search.local.HillClimber

    class HillClimber extends LocalScoreSearchAlgorithm implements Serializable
    serialVersionUID:
      4322783593818122403L

    - #### Serialized Fields

      - ##### m_bUseArcReversal

            boolean m_bUseArcReversal

        use the arc reversal operator

      - ##### m_Cache

            weka.classifiers.bayes.net.search.local.HillClimber.Cache m_Cache

        cache for storing score differences

  - ### Class weka.classifiers.bayes.net.search.local.K2

    class K2 extends LocalScoreSearchAlgorithm implements Serializable
    serialVersionUID:
      6176545934752116631L

    - #### Serialized Fields

      - ##### m_bRandomOrder

            boolean m_bRandomOrder

        Holds flag to indicate ordering should be random

  - ### Class weka.classifiers.bayes.net.search.local.LAGDHillClimber

    class LAGDHillClimber extends HillClimber implements Serializable
    serialVersionUID:
      7217437499439184344L

    - #### Serialized Fields

      - ##### m_nNrOfGoodOperations

            int m_nNrOfGoodOperations

        Number of Good Operations per Step

      - ##### m_nNrOfLookAheadSteps

            int m_nNrOfLookAheadSteps

        Number of Look Ahead Steps

  - ### Class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm

    class LocalScoreSearchAlgorithm extends SearchAlgorithm implements Serializable
    serialVersionUID:
      3325995552474190374L

    - #### Serialized Fields

      - ##### m_BayesNet

            BayesNet m_BayesNet

        points to Bayes network for which a structure is searched for

      - ##### m_fAlpha

            double m_fAlpha

        Holds prior on count

      - ##### m_nScoreType

            int m_nScoreType

        Holds the score type used to measure quality of network

  - ### Class weka.classifiers.bayes.net.search.local.RepeatedHillClimber

    class RepeatedHillClimber extends HillClimber implements Serializable
    serialVersionUID:
      -6574084564213041174L

    - #### Serialized Fields

      - ##### m_nRuns

            int m_nRuns

        number of runs

      - ##### m_nSeed

            int m_nSeed

        random number seed

      - ##### m_random

            Random m_random

        random number generator

  - ### Class weka.classifiers.bayes.net.search.local.SimulatedAnnealing

    class SimulatedAnnealing extends LocalScoreSearchAlgorithm implements Serializable
    serialVersionUID:
      6951955606060513191L

    - #### Serialized Fields

      - ##### m_bUseArcReversal

            boolean m_bUseArcReversal

        use the arc reversal operator

      - ##### m_fDelta

            double m_fDelta

        change in temperature at every run

      - ##### m_fTStart

            double m_fTStart

        start temperature

      - ##### m_nRuns

            int m_nRuns

        number of runs

      - ##### m_nSeed

            int m_nSeed

        random number seed

      - ##### m_random

            Random m_random

        random number generator

  - ### Class weka.classifiers.bayes.net.search.local.TabuSearch

    class TabuSearch extends HillClimber implements Serializable
    serialVersionUID:
      1457344073228786447L

    - #### Serialized Fields

      - ##### m_nRuns

            int m_nRuns

        number of runs

      - ##### m_nTabuList

            int m_nTabuList

        size of tabu list

      - ##### m_oTabuList

            weka.classifiers.bayes.net.search.local.HillClimber.Operation[] m_oTabuList

        the actual tabu list

  - ### Class weka.classifiers.bayes.net.search.local.TAN

    class TAN extends LocalScoreSearchAlgorithm implements Serializable
    serialVersionUID:
      965182127977228690L

- ## Package weka.classifiers.evaluation

  - ### Class weka.classifiers.evaluation.AbstractEvaluationMetric

    class AbstractEvaluationMetric extends Object implements Serializable
    serialVersionUID:
      -924507718482386887L

    - #### Serialized Fields

      - ##### m_baseEvaluation

            Evaluation m_baseEvaluation

        Base evaluation object for subclasses to access for statistics. IMPORTANT: subclasses should treat this object as read-only

  - ### Exception weka.classifiers.evaluation.AbstractEvaluationMetric.UnknownStatisticException

    class UnknownStatisticException extends IllegalArgumentException implements Serializable
    serialVersionUID:
      -8787045492227999839L

  - ### Class weka.classifiers.evaluation.AggregateableEvaluation

    class AggregateableEvaluation extends Evaluation implements Serializable
    serialVersionUID:
      8734675926526110924L

  - ### Class weka.classifiers.evaluation.ConfusionMatrix

    class ConfusionMatrix extends Matrix implements Serializable
    serialVersionUID:
      -181789981401504090L

    - #### Serialized Fields

      - ##### m_ClassNames

            String[] m_ClassNames

        Stores the names of the classes

  - ### Class weka.classifiers.evaluation.Evaluation

    class Evaluation extends Object implements Serializable
    serialVersionUID:
      -7010314486866816271L

    - #### Serialized Fields

      - ##### m_ClassIsNominal

            boolean m_ClassIsNominal

        Is the class nominal or numeric?

      - ##### m_ClassNames

            String[] m_ClassNames

        The names of the classes.

      - ##### m_ClassPriors

            double[] m_ClassPriors

        The prior probabilities of the classes.

      - ##### m_ClassPriorsSum

            double m_ClassPriorsSum

        The sum of counts for priors.

      - ##### m_ComplexityStatisticsAvailable

            boolean m_ComplexityStatisticsAvailable

        Whether complexity statistics are available.

      - ##### m_ConfLevel

            double m_ConfLevel

        The confidence level used for coverage statistics.

      - ##### m_ConfusionMatrix

            double[][] m_ConfusionMatrix

        Array for storing the confusion matrix.

      - ##### m_Correct

            double m_Correct

        The weight of all correctly classified instances.

      - ##### m_CostMatrix

            CostMatrix m_CostMatrix

        The cost matrix (if given).

      - ##### m_CoverageStatisticsAvailable

            boolean m_CoverageStatisticsAvailable

        Whether coverage statistics are available.

      - ##### m_DiscardPredictions

            boolean m_DiscardPredictions

        whether to discard predictions (and save memory).

      - ##### m_Header

            Instances m_Header

        The header of the training set.

      - ##### m_Incorrect

            double m_Incorrect

        The weight of all incorrectly classified instances.

      - ##### m_MarginCounts

            double[] m_MarginCounts

        Cumulative margin distribution.

      - ##### m_MaxTarget

            double m_MaxTarget

        Maximum target value.

      - ##### m_metricsToDisplay

            List<String> m_metricsToDisplay

        The list of metrics to display in the output

      - ##### m_MinTarget

            double m_MinTarget

        Minimum target value.

      - ##### m_MissingClass

            double m_MissingClass

        The weight of all instances that had no class assigned to them.

      - ##### m_NoPriors

            boolean m_NoPriors

        enables/disables the use of priors, e.g., if no training set is present in case of de-serialized schemes.

      - ##### m_NumClasses

            int m_NumClasses

        The number of classes.

      - ##### m_NumFolds

            int m_NumFolds

        The number of folds for a cross-validation.

      - ##### m_NumTrainClassVals

            int m_NumTrainClassVals

        Number of non-missing class training instances seen.

      - ##### m_pluginMetrics

            List<AbstractEvaluationMetric> m_pluginMetrics

        Holds plugin evaluation metrics

      - ##### m_Predictions

            ArrayList<Prediction> m_Predictions

        The list of predictions that have been generated (for computing AUC).

      - ##### m_PriorEstimator

            UnivariateKernelEstimator m_PriorEstimator

        Numeric class estimator for prior.

      - ##### m_SumAbsErr

            double m_SumAbsErr

        Sum of absolute errors.

      - ##### m_SumClass

            double m_SumClass

        Sum of class values.

      - ##### m_SumClassPredicted

            double m_SumClassPredicted

        Sum of predicted * class values.

      - ##### m_SumErr

            double m_SumErr

        Sum of errors.

      - ##### m_SumKBInfo

            double m_SumKBInfo

        Total Kononenko & Bratko Information.

      - ##### m_SumPredicted

            double m_SumPredicted

        Sum of predicted values.

      - ##### m_SumPriorAbsErr

            double m_SumPriorAbsErr

        Sum of absolute errors of the prior.

      - ##### m_SumPriorEntropy

            double m_SumPriorEntropy

        Total entropy of prior predictions.

      - ##### m_SumPriorSqrErr

            double m_SumPriorSqrErr

        Sum of absolute errors of the prior.

      - ##### m_SumSchemeEntropy

            double m_SumSchemeEntropy

        Total entropy of scheme predictions.

      - ##### m_SumSqrClass

            double m_SumSqrClass

        Sum of squared class values.

      - ##### m_SumSqrErr

            double m_SumSqrErr

        Sum of squared errors.

      - ##### m_SumSqrPredicted

            double m_SumSqrPredicted

        Sum of squared predicted values.

      - ##### m_TotalCost

            double m_TotalCost

        The total cost of predictions (includes instance weights).

      - ##### m_TotalCoverage

            double m_TotalCoverage

        Total coverage of test cases at the given confidence level.

      - ##### m_TotalSizeOfRegions

            double m_TotalSizeOfRegions

        Total size of predicted regions at the given confidence level.

      - ##### m_TrainClassVals

            double[] m_TrainClassVals

        Array containing all numeric training class values seen.

      - ##### m_TrainClassWeights

            double[] m_TrainClassWeights

        Array containing all numeric training class weights.

      - ##### m_Unclassified

            double m_Unclassified

        The weight of all unclassified instances.

      - ##### m_WithClass

            double m_WithClass

        The weight of all instances that had a class assigned to them.

  - ### Class weka.classifiers.evaluation.NominalPrediction

    class NominalPrediction extends Object implements Serializable
    serialVersionUID:
      -8871333992740492788L

    - #### Serialized Fields

      - ##### m_Actual

            double m_Actual

        The actual class value

      - ##### m_Distribution

            double[] m_Distribution

        The predicted probabilities

      - ##### m_Predicted

            double m_Predicted

        The predicted class value

      - ##### m_Weight

            double m_Weight

        The weight assigned to this prediction

  - ### Class weka.classifiers.evaluation.NumericPrediction

    class NumericPrediction extends Object implements Serializable
    serialVersionUID:
      -4880216423674233887L

    - #### Serialized Fields

      - ##### m_Actual

            double m_Actual

        The actual class value.

      - ##### m_Predicted

            double m_Predicted

        The predicted class value.

      - ##### m_PredictionIntervals

            double[][] m_PredictionIntervals

        the prediction intervals.

      - ##### m_Weight

            double m_Weight

        The weight assigned to this prediction.

- ## Package weka.classifiers.evaluation.output.prediction

  - ### Class weka.classifiers.evaluation.output.prediction.AbstractOutput

    class AbstractOutput extends Object implements Serializable
    serialVersionUID:
      752696986017306241L

    - #### Serialized Fields

      - ##### m_Attributes

            Range m_Attributes

        the range of attributes to output.

      - ##### m_Buffer

            StringBuffer m_Buffer

        the buffer to write to.

      - ##### m_FileBuffer

            StringBuffer m_FileBuffer

        the file buffer to write to.

      - ##### m_Header

            Instances m_Header

        the header of the dataset.

      - ##### m_NumDecimals

            int m_NumDecimals

        the number of decimals after the decimal point.

      - ##### m_OutputDistribution

            boolean m_OutputDistribution

        whether to output the class distribution.

      - ##### m_OutputFile

            File m_OutputFile

        the file to store the output in.

      - ##### m_SuppressOutput

            boolean m_SuppressOutput

        whether to suppress the regular output and only store in file.

  - ### Class weka.classifiers.evaluation.output.prediction.CSV

    class CSV extends AbstractOutput implements Serializable
    serialVersionUID:
      3401604538169573720L

    - #### Serialized Fields

      - ##### m_Delimiter

            String m_Delimiter

        the delimiter.

  - ### Class weka.classifiers.evaluation.output.prediction.HTML

    class HTML extends AbstractOutput implements Serializable
    serialVersionUID:
      7241252244954353300L

  - ### Class weka.classifiers.evaluation.output.prediction.InMemory

    class InMemory extends AbstractOutput implements Serializable
    serialVersionUID:
      3401604538169573720L

    - #### Serialized Fields

      - ##### m_Predictions

            List<InMemory.PredictionContainer> m_Predictions

        for storing the predictions.

  - ### Class weka.classifiers.evaluation.output.prediction.Null

    class Null extends AbstractOutput implements Serializable
    serialVersionUID:
      4988413155999044966L

  - ### Class weka.classifiers.evaluation.output.prediction.PlainText

    class PlainText extends AbstractOutput implements Serializable
    serialVersionUID:
      2033389864898242735L

  - ### Class weka.classifiers.evaluation.output.prediction.XML

    class XML extends AbstractOutput implements Serializable
    serialVersionUID:
      -3165514277316824801L

- ## Package weka.classifiers.functions

  - ### Class weka.classifiers.functions.GaussianProcesses

    class GaussianProcesses extends RandomizableClassifier implements Serializable
    serialVersionUID:
      -8620066949967678545L

    - #### Serialized Fields

      - ##### m_actualKernel

            Kernel m_actualKernel

        Actual kernel object to use

      - ##### m_Alin

            double m_Alin

        The parameters of the linear transformation realized by the filter on the class attribute

      - ##### m_avg_target

            double m_avg_target

        The training data.

      - ##### m_Blin

            double m_Blin

      - ##### m_checksTurnedOff

            boolean m_checksTurnedOff

        Turn off all checks and conversions? Turning them off assumes that data is purely numeric, doesn't contain any missing values, and has a numeric class.

      - ##### m_delta

            double m_delta

        Gaussian Noise Value.

      - ##### m_deltaSquared

            double m_deltaSquared

        The squared noise value.

      - ##### m_Filter

            Filter m_Filter

        The filter used to standardize/normalize all values.

      - ##### m_filterType

            int m_filterType

        Whether to normalize/standardize/neither

      - ##### m_kernel

            Kernel m_kernel

        Template of kernel to use

      - ##### m_L

            no.uib.cipr.matrix.Matrix m_L

        (negative) covariance matrix in symmetric matrix representation

      - ##### m_Missing

            ReplaceMissingValues m_Missing

        The filter used to get rid of missing values.

      - ##### m_NominalToBinary

            NominalToBinary m_NominalToBinary

        The filter used to make attributes numeric.

      - ##### m_NumTrain

            int m_NumTrain

        The number of training instances

      - ##### m_t

            no.uib.cipr.matrix.Vector m_t

        The vector of target values.

      - ##### m_weights

            double[] m_weights

        The weight of the training instances.

  - ### Class weka.classifiers.functions.LinearRegression

    class LinearRegression extends AbstractClassifier implements Serializable
    serialVersionUID:
      -3364580862046573747L

    - #### Serialized Fields

      - ##### m_AttributeSelection

            int m_AttributeSelection

        The current attribute selection method

      - ##### m_checksTurnedOff

            boolean m_checksTurnedOff

        Turn off all checks and conversions?

      - ##### m_ClassIndex

            int m_ClassIndex

        The index of the class attribute

      - ##### m_ClassMean

            double m_ClassMean

        The mean of the class attribute

      - ##### m_ClassStdDev

            double m_ClassStdDev

        The standard deviations of the class attribute

      - ##### m_Coefficients

            double[] m_Coefficients

        Array for storing coefficients of linear regression.

      - ##### m_df

            int m_df

        The degrees of freedom of the regression model

      - ##### m_EliminateColinearAttributes

            boolean m_EliminateColinearAttributes

        Try to eliminate correlated attributes?

      - ##### m_FStat

            double m_FStat

        The F-statistic of the regression model

      - ##### m_isZeroR

            boolean m_isZeroR

        True if the model is a zero R one

      - ##### m_Means

            double[] m_Means

        The attributes means

      - ##### m_Minimal

            boolean m_Minimal

        Conserve memory?

      - ##### m_MissingFilter

            ReplaceMissingValues m_MissingFilter

        The filter for removing missing values.

      - ##### m_ModelBuilt

            boolean m_ModelBuilt

        Model already built?

      - ##### m_outputAdditionalStats

            boolean m_outputAdditionalStats

        Whether to output additional statistics such as std. dev. of coefficients and t-stats

      - ##### m_Ridge

            double m_Ridge

        The ridge parameter

      - ##### m_RSquared

            double m_RSquared

        The R-squared value of the regression model

      - ##### m_RSquaredAdj

            double m_RSquaredAdj

        The adjusted R-squared value of the regression model

      - ##### m_SelectedAttributes

            boolean[] m_SelectedAttributes

        Which attributes are relevant?

      - ##### m_StdDevs

            double[] m_StdDevs

        The attribute standard deviations

      - ##### m_StdErrorOfCoef

            double[] m_StdErrorOfCoef

        Array for storing the standard error of each coefficient

      - ##### m_TransformedData

            Instances m_TransformedData

        Variable for storing transformed training data.

      - ##### m_TransformFilter

            NominalToBinary m_TransformFilter

        The filter storing the transformation from nominal to binary attributes.

      - ##### m_TStats

            double[] m_TStats

        Array for storing the t-statistic of each coefficient

      - ##### m_useQRDecomposition

            boolean m_useQRDecomposition

        Use QR decomposition

  - ### Class weka.classifiers.functions.Logistic

    class Logistic extends AbstractClassifier implements Serializable
    serialVersionUID:
      3932117032546553727L

    - #### Serialized Fields

      - ##### m_AttFilter

            RemoveUseless m_AttFilter

        An attribute filter

      - ##### m_ClassIndex

            int m_ClassIndex

        The index of the class attribute

      - ##### m_Data

            double[][] m_Data

        The data saved as a matrix

      - ##### m_doNotStandardizeAttributes

            boolean m_doNotStandardizeAttributes

        Whether to turn of standardization of attributes.

      - ##### m_LL

            double m_LL

        Log-likelihood of the searched model

      - ##### m_MaxIts

            int m_MaxIts

        The maximum number of iterations.

      - ##### m_NominalToBinary

            NominalToBinary m_NominalToBinary

        The filter used to make attributes numeric.

      - ##### m_NumClasses

            int m_NumClasses

        The number of the class labels

      - ##### m_numModels

            int m_numModels

      - ##### m_NumPredictors

            int m_NumPredictors

        The number of attributes in the model

      - ##### m_Par

            double[][] m_Par

        The coefficients (optimized parameters) of the model

      - ##### m_ReplaceMissingValues

            ReplaceMissingValues m_ReplaceMissingValues

        The filter used to get rid of missing values.

      - ##### m_Ridge

            double m_Ridge

        The ridge parameter.

      - ##### m_structure

            Instances m_structure

        The header information in the training data.

      - ##### m_useConjugateGradientDescent

            boolean m_useConjugateGradientDescent

        Whether to use conjugate gradient descent rather than BFGS updates.

  - ### Class weka.classifiers.functions.MultilayerPerceptron

    class MultilayerPerceptron extends AbstractClassifier implements Serializable
    serialVersionUID:
      -5990607817048210779L

    - #### Serialized Fields

      - ##### bestError

            double bestError

      - ##### driftOff

            double driftOff

        Drift off counter

      - ##### lastRight

            double lastRight

        To keep track of error

      - ##### m_accepted

            boolean m_accepted

        a flag to state that the network should be accepted the way it is.

      - ##### m_attributeBases

            double[] m_attributeBases

        The base values for all the attributes.

      - ##### m_attributeRanges

            double[] m_attributeRanges

        The ranges for all the attributes.

      - ##### m_autoBuild

            boolean m_autoBuild

        A flag to tell the build classifier to automatically build a neural net.

      - ##### m_currentInstance

            Instance m_currentInstance

        The current instance running through the network.

      - ##### m_decay

            boolean m_decay

        This flag states that the user wants the learning rate to decay.

      - ##### m_driftThreshold

            int m_driftThreshold

        The number to to use to quit on validation testing.

      - ##### m_epoch

            int m_epoch

        Shows the number of the epoch that the network just finished.

      - ##### m_error

            double m_error

        Shows the error of the epoch that the network just finished.

      - ##### m_gui

            boolean m_gui

        A flag to state that the gui for the network should be brought up. To allow interaction while training.

      - ##### m_hiddenLayers

            String m_hiddenLayers

        The string that defines the hidden layers

      - ##### m_inputs

            weka.classifiers.functions.MultilayerPerceptron.NeuralEnd[] m_inputs

        The input units.(only feeds the inputs does no calcs)

      - ##### m_instances

            Instances m_instances

        The training instances.

      - ##### m_learningRate

            double m_learningRate

        This is the learning rate for the network.

      - ##### m_linearUnit

            LinearUnit m_linearUnit

        This is a linear unit.

      - ##### m_momentum

            double m_momentum

        This is the momentum for the network.

      - ##### m_neuralNodes

            NeuralConnection[] m_neuralNodes

        All the nodes that actually comprise the logical neural net.

      - ##### m_nextId

            int m_nextId

        The next id number available for default naming.

      - ##### m_nominalToBinaryFilter

            NominalToBinary m_nominalToBinaryFilter

        The actual filter.

      - ##### m_normalizeAttributes

            boolean m_normalizeAttributes

        This flag states that the user wants the input values normalized.

      - ##### m_normalizeClass

            boolean m_normalizeClass

        This flag states that the user wants the class to be normalized while processing in the network is done. (the final answer will be in the original range regardless). This option will only be used when the class is numeric.

      - ##### m_numAttributes

            int m_numAttributes

        The number of attributes.

      - ##### m_numClasses

            int m_numClasses

        The number of classes.

      - ##### m_numEpochs

            int m_numEpochs

        The number of epochs to train through.

      - ##### m_numeric

            boolean m_numeric

        A flag to say that it's a numeric class.

      - ##### m_numItsPerformed

            int m_numItsPerformed

        Number of iterations (epochs) performed in this session of iterating

      - ##### m_outputs

            weka.classifiers.functions.MultilayerPerceptron.NeuralEnd[] m_outputs

        The output units.(only feeds the errors, does no calcs)

      - ##### m_random

            Random m_random

        The actual random number generator.

      - ##### m_randomSeed

            int m_randomSeed

        The number used to seed the random number generator.

      - ##### m_reset

            boolean m_reset

        This flag states that the user wants the network to restart if it is found to be generating infinity or NaN for the error value. This would restart the network with the current options except that the learning rate would be smaller than before, (perhaps half of its current value). This option will not be available if the gui is chosen (if the gui is open the user can fix the network themselves, it is an architectural minefield for the network to be reset with the gui open).

      - ##### m_resume

            boolean m_resume

        Whether to allow training to continue at a later point after the initial model is built.

      - ##### m_selected

            ArrayList<NeuralConnection> m_selected

        A Vector list of the units currently selected.

      - ##### m_sigmoidUnit

            SigmoidUnit m_sigmoidUnit

        this is a sigmoid unit.

      - ##### m_stopIt

            boolean m_stopIt

        a flag to state if the network should be running, or stopped.

      - ##### m_stopped

            boolean m_stopped

        a flag to state that the network has in fact stopped.

      - ##### m_useDefaultModel

            boolean m_useDefaultModel

        Whether to use the default ZeroR model

      - ##### m_useNomToBin

            boolean m_useNomToBin

        A flag to state that a nominal to binary filter should be used.

      - ##### m_valSize

            int m_valSize

        An int to say how big the validation set should be.

      - ##### m_ZeroR

            Classifier m_ZeroR

        a ZeroR model in case no model can be built from the data or the network predicts all zeros for the classes

      - ##### numInVal

            int numInVal

        The number of instances in the validation set (if any)

      - ##### originalFormatData

            Instances originalFormatData

        Data in original format (in case learning rate gets reset

      - ##### totalValWeight

            double totalValWeight

        Total weight of the instances in the validation set (if any)

      - ##### totalWeight

            double totalWeight

        Total weight of the instances in the training set

      - ##### valSet

            Instances valSet

        The instances in the validation set (if any)

  - ### Class weka.classifiers.functions.MultilayerPerceptron.NeuralEnd

    class NeuralEnd extends NeuralConnection implements Serializable
    serialVersionUID:
      7305185603191183338L

    - #### Serialized Fields

      - ##### m_input

            boolean m_input

        True if node is an input, False if it's an output.

      - ##### m_link

            int m_link

        the value that represents the instance value this node represents. For an input it is the attribute number, for an output, if nominal it is the class value.

  - ### Class weka.classifiers.functions.SGD

    class SGD extends RandomizableClassifier implements Serializable
    serialVersionUID:
      -3732968666673530290L

    - #### Serialized Fields

      - ##### m_data

            Instances m_data

        Holds the header of the training data

      - ##### m_dontNormalize

            boolean m_dontNormalize

        Turn off normalization of the input data. This option gets forced for incremental training.

      - ##### m_dontReplaceMissing

            boolean m_dontReplaceMissing

        Turn off global replacement of missing values. Missing values will be ignored instead. This option gets forced for incremental training.

      - ##### m_epochs

            int m_epochs

        The number of epochs to perform (batch learning). Total iterations is m_epochs * num instances

      - ##### m_epsilon

            double m_epsilon

        The epsilon parameter for epsilon insensitive and Huber loss

      - ##### m_lambda

            double m_lambda

        The regularization parameter

      - ##### m_learningRate

            double m_learningRate

        The learning rate

      - ##### m_loss

            int m_loss

        The current loss function to minimize

      - ##### m_nominalToBinary

            Filter m_nominalToBinary

        Convert nominal attributes to numerically coded binary ones. Uses supervised NominalToBinary in the batch learning case

      - ##### m_normalize

            Normalize m_normalize

        Normalize the training data

      - ##### m_numInstances

            double m_numInstances

        The number of training instances

      - ##### m_numModels

            int m_numModels

      - ##### m_replaceMissing

            ReplaceMissingValues m_replaceMissing

        Replace missing values

      - ##### m_t

            double m_t

        Holds the current iteration number

      - ##### m_weights

            double[] m_weights

        Stores the weights (+ bias in the last element)

  - ### Class weka.classifiers.functions.SGDText

    class SGDText extends RandomizableClassifier implements Serializable
    serialVersionUID:
      7200171484002029584L

    - #### Serialized Fields

      - ##### m_bias

            double m_bias

        Holds the bias term

      - ##### m_data

            Instances m_data

        The header of the training data

      - ##### m_dictionary

            LinkedHashMap<String,SGDText.Count> m_dictionary

        The dictionary (and term weights)

      - ##### m_epochs

            int m_epochs

        The number of epochs to perform (batch learning). Total iterations is m_epochs * num instances

      - ##### m_fitLogistic

            boolean m_fitLogistic

        True if a logistic regression is to be fit to the output of the SVM for producing probability estimates

      - ##### m_fitLogisticStructure

            Instances m_fitLogisticStructure

      - ##### m_lambda

            double m_lambda

        The regularization parameter

      - ##### m_learningRate

            double m_learningRate

        The learning rate

      - ##### m_lnorm

            double m_lnorm

        The L-norm to use

      - ##### m_loss

            int m_loss

        The current loss function to minimize

      - ##### m_lowercaseTokens

            boolean m_lowercaseTokens

        Whether or not to convert all tokens to lowercase

      - ##### m_minAbsCoefficient

            double m_minAbsCoefficient

        Prune terms from the model that have a coefficient smaller than this.

      - ##### m_minWordP

            double m_minWordP

        Only consider dictionary words (features) that occur at least this many times.

      - ##### m_norm

            double m_norm

        The length that each document vector should have in the end

      - ##### m_normalize

            boolean m_normalize

        Whether to normalized document length or not

      - ##### m_numInstances

            double m_numInstances

        The number of training instances

      - ##### m_numModels

            int m_numModels

      - ##### m_periodicP

            int m_periodicP

        The number of training instances at which to periodically prune the dictionary of min frequency words. Empty or null string indicates don't prune

      - ##### m_stemmer

            Stemmer m_stemmer

        The stemming algorithm.

      - ##### m_StopwordsHandler

            StopwordsHandler m_StopwordsHandler

        Stopword handler to use.

      - ##### m_svmProbs

            SGD m_svmProbs

        Used for producing probabilities for SVM via SGD logistic regression

      - ##### m_t

            double m_t

        Holds the current iteration number

      - ##### m_tokenizer

            Tokenizer m_tokenizer

        The tokenizer to use

      - ##### m_wordFrequencies

            boolean m_wordFrequencies

        Use word frequencies rather than bag-of-words if true

  - ### Class weka.classifiers.functions.SGDText.Count

    class Count extends Object implements Serializable
    serialVersionUID:
      2104201532017340967L

    - #### Serialized Fields

      - ##### m_count

            double m_count

      - ##### m_weight

            double m_weight

  - ### Class weka.classifiers.functions.SimpleLinearRegression

    class SimpleLinearRegression extends AbstractClassifier implements Serializable
    serialVersionUID:
      1679336022895414137L

    - #### Serialized Fields

      - ##### m_attribute

            Attribute m_attribute

        The chosen attribute

      - ##### m_attributeIndex

            int m_attributeIndex

        The index of the chosen attribute

      - ##### m_classMeanForMissing

            double m_classMeanForMissing

        The class mean for missing values

      - ##### m_df

            int m_df

        Degrees of freedom, used in statistical calculations

      - ##### m_fstat

            double m_fstat

        F-statistic for the regression

      - ##### m_intercept

            double m_intercept

        The intercept

      - ##### m_outputAdditionalStats

            boolean m_outputAdditionalStats

        Whether to output additional statistics such as std. dev. of coefficients and t-stats

      - ##### m_rsquared

            double m_rsquared

        R^2 value for the regression

      - ##### m_rsquaredAdj

            double m_rsquaredAdj

        Adjusted R^2 value for the regression

      - ##### m_seIntercept

            double m_seIntercept

        standard error of the intercept

      - ##### m_seSlope

            double m_seSlope

        standard error of the slope

      - ##### m_slope

            double m_slope

        The slope

      - ##### m_suppressErrorMessage

            boolean m_suppressErrorMessage

        If true, suppress error message if no useful attribute was found

      - ##### m_tstatIntercept

            double m_tstatIntercept

        t-statistic of the intercept

      - ##### m_tstatSlope

            double m_tstatSlope

        t-statistic of the slope

  - ### Class weka.classifiers.functions.SimpleLogistic

    class SimpleLogistic extends AbstractClassifier implements Serializable
    serialVersionUID:
      7397710626304705059L

    - #### Serialized Fields

      - ##### m_boostedModel

            LogisticBase m_boostedModel

        The actual logistic regression model

      - ##### m_errorOnProbabilities

            boolean m_errorOnProbabilities

        If true, use minimize error on probabilities instead of misclassification error

      - ##### m_heuristicStop

            int m_heuristicStop

        Parameter for the heuristic for early stopping of LogitBoost

      - ##### m_maxBoostingIterations

            int m_maxBoostingIterations

        Maximum number of iterations for LogitBoost

      - ##### m_NominalToBinary

            NominalToBinary m_NominalToBinary

        Filter for converting nominal attributes to binary ones

      - ##### m_numBoostingIterations

            int m_numBoostingIterations

        If non-negative, use this as fixed number of LogitBoost iterations

      - ##### m_ReplaceMissingValues

            ReplaceMissingValues m_ReplaceMissingValues

        Filter for replacing missing values

      - ##### m_useAIC

            boolean m_useAIC

        If true, the AIC is used to choose the best iteration

      - ##### m_useCrossValidation

            boolean m_useCrossValidation

        If true, cross-validate number of LogitBoost iterations

      - ##### m_weightTrimBeta

            double m_weightTrimBeta

        Threshold for trimming weights. Instances with a weight lower than this (as a percentage of total weights) are not included in the regression fit.

  - ### Class weka.classifiers.functions.SMO

    class SMO extends AbstractClassifier implements Serializable
    serialVersionUID:
      -6585883636378691736L

    - #### Serialized Fields

      - ##### m_C

            double m_C

        The complexity parameter.

      - ##### m_calibrator

            Classifier m_calibrator

        Determines the calibrator model to use for probability estimate

      - ##### m_checksTurnedOff

            boolean m_checksTurnedOff

        Turn off all checks and conversions? Turning them off assumes that data is purely numeric, doesn't contain any missing values, and has a nominal class. Turning them off also means that no header information will be stored if the machine is linear. Finally, it also assumes that no instance has a weight equal to 0.

      - ##### m_classAttribute

            Attribute m_classAttribute

        The class attribute

      - ##### m_classifiers

            SMO.BinarySMO[][] m_classifiers

        The binary classifier(s)

      - ##### m_classIndex

            int m_classIndex

        The class index from the training data

      - ##### m_eps

            double m_eps

        Epsilon for rounding.

      - ##### m_Filter

            Filter m_Filter

        The filter used to standardize/normalize all values.

      - ##### m_filterType

            int m_filterType

        Whether to normalize/standardize/neither

      - ##### m_fitCalibratorModels

            boolean m_fitCalibratorModels

        Whether calibrator models are to be fit

      - ##### m_kernel

            Kernel m_kernel

        the kernel to use

      - ##### m_KernelIsLinear

            boolean m_KernelIsLinear

        whether the kernel is a linear one

      - ##### m_Missing

            ReplaceMissingValues m_Missing

        The filter used to get rid of missing values.

      - ##### m_NominalToBinary

            NominalToBinary m_NominalToBinary

        The filter used to make attributes numeric.

      - ##### m_numFolds

            int m_numFolds

        The number of folds for the internal cross-validation

      - ##### m_randomSeed

            int m_randomSeed

        The random number seed

      - ##### m_tol

            double m_tol

        Tolerance for accuracy of result.

  - ### Class weka.classifiers.functions.SMO.BinarySMO

    class BinarySMO extends Object implements Serializable
    serialVersionUID:
      -8246163625699362456L

    - #### Serialized Fields

      - ##### m_alpha

            double[] m_alpha

        The Lagrange multipliers.

      - ##### m_b

            double m_b

        The thresholds.

      - ##### m_bLow

            double m_bLow

        The thresholds.

      - ##### m_bUp

            double m_bUp

        The thresholds.

      - ##### m_calibrationDataHeader

            Instances m_calibrationDataHeader

        Reference to the header information for the calibration data

      - ##### m_calibrator

            Classifier m_calibrator

        Stores calibrator model for probability estimate

      - ##### m_class

            double[] m_class

        The transformed class values.

      - ##### m_data

            Instances m_data

        The training data.

      - ##### m_errors

            double[] m_errors

        The current set of errors for all non-bound examples.

      - ##### m_I0

            SMOset m_I0

        {i: 0 < m_alpha[i] < C}

      - ##### m_I1

            SMOset m_I1

        {i: m_class[i] = 1, m_alpha[i] = 0}

      - ##### m_I2

            SMOset m_I2

        {i: m_class[i] = -1, m_alpha[i] =C}

      - ##### m_I3

            SMOset m_I3

        {i: m_class[i] = 1, m_alpha[i] = C}

      - ##### m_I4

            SMOset m_I4

        {i: m_class[i] = -1, m_alpha[i] = 0}

      - ##### m_iLow

            int m_iLow

        The indices for m_bLow and m_bUp

      - ##### m_iUp

            int m_iUp

        The indices for m_bLow and m_bUp

      - ##### m_kernel

            Kernel m_kernel

        Kernel to use

      - ##### m_nCacheHits

            int m_nCacheHits

        number of kernel cache hits, used for printing statistics only

      - ##### m_nEvals

            long m_nEvals

        number of kernel evaluations, used for printing statistics only

      - ##### m_sparseIndices

            int[] m_sparseIndices

      - ##### m_sparseWeights

            double[] m_sparseWeights

        Variables to hold weight vector in sparse form. (To reduce storage requirements.)

      - ##### m_sumOfWeights

            double m_sumOfWeights

        Stores the weight of the training instances

      - ##### m_supportVectors

            SMOset m_supportVectors

        The set of support vectors

      - ##### m_weights

            double[] m_weights

        Weight vector for linear machine.

  - ### Class weka.classifiers.functions.SMOreg

    class SMOreg extends AbstractClassifier implements Serializable
    serialVersionUID:
      -7149606251113102827L

    - #### Serialized Fields

      - ##### m_C

            double m_C

        capacity parameter

      - ##### m_Filter

            Filter m_Filter

        The filter used to standardize/normalize all values.

      - ##### m_filterType

            int m_filterType

        Whether to normalize/standardize/neither

      - ##### m_kernel

            Kernel m_kernel

        the configured kernel

      - ##### m_Missing

            ReplaceMissingValues m_Missing

        The filter used to get rid of missing values.

      - ##### m_NominalToBinary

            NominalToBinary m_NominalToBinary

        The filter used to make attributes numeric.

      - ##### m_onlyNumeric

            boolean m_onlyNumeric

        Only numeric attributes in the dataset? If so, less need to filter

      - ##### m_optimizer

            RegOptimizer m_optimizer

        contains the algorithm used for learning

      - ##### m_x0

            double m_x0

      - ##### m_x1

            double m_x1

        coefficients used by normalization filter for doing its linear transformation so that result = svmoutput * m_x1 + m_x0

  - ### Class weka.classifiers.functions.VotedPerceptron

    class VotedPerceptron extends AbstractClassifier implements Serializable
    serialVersionUID:
      -1072429260104568698L

    - #### Serialized Fields

      - ##### m_Additions

            int[] m_Additions

        The training instances added to the perceptron

      - ##### m_Exponent

            double m_Exponent

        The exponent

      - ##### m_IsAddition

            boolean[] m_IsAddition

        Addition or subtraction?

      - ##### m_K

            int m_K

        The actual number of alterations

      - ##### m_MaxK

            int m_MaxK

        The maximum number of alterations to the perceptron

      - ##### m_NominalToBinary

            NominalToBinary m_NominalToBinary

        The filter used to make attributes numeric.

      - ##### m_NumIterations

            int m_NumIterations

        The number of iterations

      - ##### m_ReplaceMissingValues

            ReplaceMissingValues m_ReplaceMissingValues

        The filter used to get rid of missing values.

      - ##### m_Seed

            int m_Seed

        Seed used for shuffling the dataset

      - ##### m_Train

            Instances m_Train

        The training instances

      - ##### m_Weights

            int[] m_Weights

        The weights for each perceptron

- ## Package weka.classifiers.functions.neural

  - ### Class weka.classifiers.functions.neural.LinearUnit

    class LinearUnit extends Object implements Serializable
    serialVersionUID:
      8572152807755673630L

  - ### Class weka.classifiers.functions.neural.NeuralConnection

    class NeuralConnection extends Object implements Serializable
    serialVersionUID:
      -286208828571059163L

    - #### Serialized Fields

      - ##### m_id

            String m_id

        The string that uniquely (provided naming is done properly) identifies this unit.

      - ##### m_inputList

            NeuralConnection[] m_inputList

        The list of inputs to this unit.

      - ##### m_inputNums

            int[] m_inputNums

        The numbering for the connections at the other end of the input lines.

      - ##### m_numInputs

            int m_numInputs

        The number of inputs.

      - ##### m_numOutputs

            int m_numOutputs

        The number of outputs.

      - ##### m_outputList

            NeuralConnection[] m_outputList

        The list of outputs from this unit.

      - ##### m_outputNums

            int[] m_outputNums

        The numbering for the connections at the other end of the out lines.

      - ##### m_type

            int m_type

        The type of unit this is.

      - ##### m_unitError

            double m_unitError

        The error value for this unit, NaN if not calculated.

      - ##### m_unitValue

            double m_unitValue

        The output value for this unit, NaN if not calculated.

      - ##### m_weightsUpdated

            boolean m_weightsUpdated

        True if the weights have already been updated.

      - ##### m_x

            double m_x

        The x coord of this unit purely for displaying purposes.

      - ##### m_y

            double m_y

        The y coord of this unit purely for displaying purposes.

  - ### Class weka.classifiers.functions.neural.NeuralNode

    class NeuralNode extends NeuralConnection implements Serializable
    serialVersionUID:
      -1085750607680839163L

    - #### Serialized Fields

      - ##### m_bestWeights

            double[] m_bestWeights

        The best (lowest error) weights. Only used when validation set is used

      - ##### m_changeInWeights

            double[] m_changeInWeights

        The change in the weights.

      - ##### m_methods

            NeuralMethod m_methods

        Performs the operations for this node. Currently this defines that the node is either a sigmoid or a linear unit.

      - ##### m_random

            Random m_random

      - ##### m_weights

            double[] m_weights

        The weights for each of the input connections, and the threshold.

  - ### Class weka.classifiers.functions.neural.SigmoidUnit

    class SigmoidUnit extends Object implements Serializable
    serialVersionUID:
      -5162958458177475652L

- ## Package weka.classifiers.functions.supportVector

  - ### Class weka.classifiers.functions.supportVector.CachedKernel

    class CachedKernel extends Kernel implements Serializable
    serialVersionUID:
      702810182699015136L

    - #### Serialized Fields

      - ##### m_cacheHits

            int m_cacheHits

        Counts the number of kernel cache hits.

      - ##### m_cacheSize

            int m_cacheSize

        The size of the cache (a prime number)

      - ##### m_cacheSlots

            int m_cacheSlots

        number of cache slots in an entry

      - ##### m_kernelEvals

            int m_kernelEvals

        Counts the number of kernel evaluations.

      - ##### m_kernelMatrix

            double[][] m_kernelMatrix

        The kernel matrix if full cache is used (i.e. size is set to 0)

      - ##### m_keys

            long[] m_keys

      - ##### m_numInsts

            int m_numInsts

        The number of instance in the dataset

      - ##### m_storage

            double[] m_storage

        Kernel cache

  - ### Class weka.classifiers.functions.supportVector.Kernel

    class Kernel extends Object implements Serializable
    serialVersionUID:
      -6102771099905817064L

    - #### Serialized Fields

      - ##### m_ChecksTurnedOff

            boolean m_ChecksTurnedOff

        This value is now ignored. Checks are always turned off as they are the responsibility of the class using the kernel. We are keeping this to allow deserialization.

      - ##### m_data

            Instances m_data

        The dataset

      - ##### m_Debug

            boolean m_Debug

        enables debugging output

      - ##### m_DoNotCheckCapabilities

            boolean m_DoNotCheckCapabilities

        This value is now ignored. Checks are always turned off as they are the responsibility of the class using the kernel. We are keeping this to allow deserialization.

  - ### Class weka.classifiers.functions.supportVector.NormalizedPolyKernel

    class NormalizedPolyKernel extends PolyKernel implements Serializable
    serialVersionUID:
      1248574185532130851L

    - #### Serialized Fields

      - ##### m_diagDotproducts

            double[] m_diagDotproducts

        A cache for the diagonal of the dot product kernel

  - ### Class weka.classifiers.functions.supportVector.PolyKernel

    class PolyKernel extends CachedKernel implements Serializable
    serialVersionUID:
      -321831645846363201L

    - #### Serialized Fields

      - ##### m_exponent

            double m_exponent

        The exponent for the polynomial kernel.

      - ##### m_lowerOrder

            boolean m_lowerOrder

        Use lower-order terms?

  - ### Class weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel

    class PrecomputedKernelMatrixKernel extends Kernel implements Serializable
    serialVersionUID:
      -321831645846363333L

    - #### Serialized Fields

      - ##### m_Counter

            int m_Counter

        A classifier counter.

      - ##### m_KernelMatrix

            Matrix m_KernelMatrix

        The kernel matrix.

      - ##### m_KernelMatrixFile

            File m_KernelMatrixFile

        The file holding the kernel matrix.

  - ### Class weka.classifiers.functions.supportVector.Puk

    class Puk extends CachedKernel implements Serializable
    serialVersionUID:
      1682161522559978851L

    - #### Serialized Fields

      - ##### m_factor

            double m_factor

        Cached factor for the Puk kernel.

      - ##### m_kernelPrecalc

            double[] m_kernelPrecalc

        The precalculated dotproducts of <inst_i,inst_i>

      - ##### m_omega

            double m_omega

        Omega for the Puk kernel.

      - ##### m_sigma

            double m_sigma

        Sigma for the Puk kernel.

  - ### Class weka.classifiers.functions.supportVector.RBFKernel

    class RBFKernel extends CachedKernel implements Serializable
    serialVersionUID:
      5247117544316387852L

    - #### Serialized Fields

      - ##### m_gamma

            double m_gamma

        The gamma parameter for the RBF kernel.

      - ##### m_kernelPrecalc

            double[] m_kernelPrecalc

        The diagonal values of the dot product matrix (name needs to be consistent with J. Lindgren's implementation).

  - ### Class weka.classifiers.functions.supportVector.RegOptimizer

    class RegOptimizer extends Object implements Serializable
    serialVersionUID:
      -2198266997254461814L

    - #### Serialized Fields

      - ##### m_alpha

            double[] m_alpha

        alpha and alpha* arrays containing weights for solving dual problem

      - ##### m_alphaStar

            double[] m_alphaStar

      - ##### m_b

            double m_b

        offset

      - ##### m_bModelBuilt

            boolean m_bModelBuilt

        flag to indicate whether the model is built yet

      - ##### m_C

            double m_C

        capacity parameter, copied from SMOreg

      - ##### m_classIndex

            int m_classIndex

        index of class variable in data set

      - ##### m_data

            Instances m_data

        points to data set

      - ##### m_epsilon

            double m_epsilon

        epsilon of epsilon-insensitive cost function

      - ##### m_kernel

            Kernel m_kernel

        the kernel

      - ##### m_nCacheHits

            int m_nCacheHits

        number of kernel cache hits, used for printing statistics only

      - ##### m_nEvals

            long m_nEvals

        number of kernel evaluations, used for printing statistics only

      - ##### m_nInstances

            int m_nInstances

        number of instances in data set

      - ##### m_nSeed

            int m_nSeed

        seed for initializing random number generator

      - ##### m_random

            Random m_random

        random number generator

      - ##### m_sparseIndices

            int[] m_sparseIndices

      - ##### m_sparseWeights

            double[] m_sparseWeights

        Variables to hold weight vector in sparse form. (To reduce storage requirements.)

      - ##### m_supportVectors

            SMOset m_supportVectors

        set of support vectors, that is, vectors with alpha(*)!=0

      - ##### m_SVM

            SMOreg m_SVM

        parent SMOreg class

      - ##### m_target

            double[] m_target

        class values/desired output vector

      - ##### m_weights

            double[] m_weights

        weights for linear kernel

  - ### Class weka.classifiers.functions.supportVector.RegSMO

    class RegSMO extends RegOptimizer implements Serializable
    serialVersionUID:
      -7504070793279598638L

    - #### Serialized Fields

      - ##### m_alpha1

            double m_alpha1

        alpha value for first candidate

      - ##### m_alpha1Star

            double m_alpha1Star

        alpha* value for first candidate

      - ##### m_alpha2

            double m_alpha2

        alpha value for second candidate

      - ##### m_alpha2Star

            double m_alpha2Star

        alpha* value for second candidate

      - ##### m_eps

            double m_eps

        tolerance parameter, smaller changes on alpha in inner loop will be ignored

      - ##### m_error

            double[] m_error

        error cache containing m_error[i] = SVMOutput(i) - m_target[i] - m_b
        note, we don't need m_b in the cache, since if we do, we need to maintain it when m_b is updated

  - ### Class weka.classifiers.functions.supportVector.RegSMOImproved

    class RegSMOImproved extends RegSMO implements Serializable
    serialVersionUID:
      471692841446029784L

    - #### Serialized Fields

      - ##### m_bLow

            double m_bLow

        b.up and b.low boundaries used to determine stopping criterion

      - ##### m_bUp

            double m_bUp

        b.up and b.low boundaries used to determine stopping criterion

      - ##### m_bUseVariant1

            boolean m_bUseVariant1

        set true to use variant 1 of the paper, otherwise use variant 2

      - ##### m_fTolerance

            double m_fTolerance

        tolerance parameter used for checking stopping criterion b.up < b.low + 2 tol

      - ##### m_I0

            SMOset m_I0

        The different sets used by the algorithm.

      - ##### m_iLow

            int m_iLow

        index of the instance that gave us b.up and b.low

      - ##### m_iSet

            int[] m_iSet

        Index set {i: 0 < m_alpha[i] < C || 0 < m_alphaStar[i] < C}}

      - ##### m_iUp

            int m_iUp

        index of the instance that gave us b.up and b.low

  - ### Class weka.classifiers.functions.supportVector.SMOset

    class SMOset extends Object implements Serializable
    serialVersionUID:
      -8364829283188675777L

    - #### Serialized Fields

      - ##### m_first

            int m_first

        The first element in the set

      - ##### m_indicators

            boolean[] m_indicators

        Indicators

      - ##### m_next

            int[] m_next

        The next element for each element

      - ##### m_number

            int m_number

        The current number of elements in the set

      - ##### m_previous

            int[] m_previous

        The previous element for each element

  - ### Class weka.classifiers.functions.supportVector.StringKernel

    class StringKernel extends Kernel implements Serializable
    serialVersionUID:
      -4902954211202690123L

    - #### Serialized Fields

      - ##### cachekh

            double[] cachekh

      - ##### cachekh2

            double[] cachekh2

      - ##### cachekh2K

            int[] cachekh2K

      - ##### cachekhK

            int[] cachekhK

      - ##### m_cacheSize

            int m_cacheSize

        The size of the cache (a prime number)

      - ##### m_internalCacheSize

            int m_internalCacheSize

        The size of the internal cache for intermediate results (a prime number)

      - ##### m_kernelEvals

            int m_kernelEvals

        Counts the number of kernel evaluations.

      - ##### m_keys

            long[] m_keys

      - ##### m_lambda

            double m_lambda

        the decay factor that penalizes non-continuous substring matches. See [1] for details.

      - ##### m_maxSubsequenceLength

            int m_maxSubsequenceLength

        The maximum substring length for lambda pruning

      - ##### m_multX

            int m_multX

        cached indexes for private cache

      - ##### m_multY

            int m_multY

      - ##### m_multZ

            int m_multZ

      - ##### m_multZZ

            int m_multZZ

      - ##### m_normalize

            boolean m_normalize

        flag for switching normalization on or off. This defaults to false and can be turned on by the switch for feature space normalization in SMO

      - ##### m_numInsts

            int m_numInsts

        The number of instance in the dataset

      - ##### m_powersOflambda

            double[] m_powersOflambda

        the precalculated powers of lambda

      - ##### m_PruningMethod

            int m_PruningMethod

        the pruning method

      - ##### m_storage

            double[] m_storage

        Kernel cache (i.e., cache for kernel evaluations)

      - ##### m_strAttr

            int m_strAttr

        The attribute number of the string attribute

      - ##### m_subsequenceLength

            int m_subsequenceLength

        The substring length

      - ##### m_useRecursionCache

            boolean m_useRecursionCache

      - ##### maxCache

            int maxCache

        private cache for intermediate results

- ## Package weka.classifiers.lazy

  - ### Class weka.classifiers.lazy.IBk

    class IBk extends AbstractClassifier implements Serializable
    serialVersionUID:
      -3080186098777067172L

    - #### Serialized Fields

      - ##### m_ClassType

            int m_ClassType

        The class attribute type.

      - ##### m_CrossValidate

            boolean m_CrossValidate

        Whether to select k by cross validation.

      - ##### m_defaultModel

            ZeroR m_defaultModel

        Default ZeroR model to use when there are no training instances

      - ##### m_DistanceWeighting

            int m_DistanceWeighting

        Whether the neighbours should be distance-weighted.

      - ##### m_kNN

            int m_kNN

        The number of neighbours to use for classification (currently).

      - ##### m_kNNUpper

            int m_kNNUpper

        The value of kNN provided by the user. This may differ from m_kNN if cross-validation is being used.

      - ##### m_kNNValid

            boolean m_kNNValid

        Whether the value of k selected by cross validation has been invalidated by a change in the training instances.

      - ##### m_MeanSquared

            boolean m_MeanSquared

        Whether to minimise mean squared error rather than mean absolute error when cross-validating on numeric prediction tasks.

      - ##### m_NNSearch

            NearestNeighbourSearch m_NNSearch

        for nearest-neighbor search.

      - ##### m_NumAttributesUsed

            double m_NumAttributesUsed

        The number of attributes the contribute to a prediction.

      - ##### m_NumClasses

            int m_NumClasses

        The number of class values (or 1 if predicting numeric).

      - ##### m_Train

            Instances m_Train

        The training instances used for classification.

      - ##### m_WindowSize

            int m_WindowSize

        The maximum number of training instances allowed. When this limit is reached, old training instances are removed, so the training data is "windowed". Set to 0 for unlimited numbers of instances.

  - ### Class weka.classifiers.lazy.KStar

    class KStar extends AbstractClassifier implements Serializable
    serialVersionUID:
      332458330800479083L

    - #### Serialized Fields

      - ##### m_BlendMethod

            int m_BlendMethod

        0 = use specified blend, 1 = entropic blend setting

      - ##### m_Cache

            KStarCache[] m_Cache

        A custom data structure for caching distinct attribute values and their scale factor or stop parameter.

      - ##### m_ClassType

            int m_ClassType

        The class attribute type

      - ##### m_ComputeRandomCols

            int m_ComputeRandomCols

        Flag turning on and off the computation of random class colomns

      - ##### m_GlobalBlend

            int m_GlobalBlend

        default sphere of influence blend setting

      - ##### m_InitFlag

            int m_InitFlag

        Flag turning on and off the initialisation of config variables

      - ##### m_MissingMode

            int m_MissingMode

        missing value treatment

      - ##### m_NumAttributes

            int m_NumAttributes

        The number of attributes

      - ##### m_NumClasses

            int m_NumClasses

        The number of class values

      - ##### m_NumInstances

            int m_NumInstances

        The number of instances in the dataset

      - ##### m_RandClassCols

            int[][] m_RandClassCols

        Table of random class value colomns

      - ##### m_Train

            Instances m_Train

        The training instances used for classification.

  - ### Class weka.classifiers.lazy.LWL

    class LWL extends SingleClassifierEnhancer implements Serializable
    serialVersionUID:
      1979797405383665815L

    - #### Serialized Fields

      - ##### m_kNN

            int m_kNN

        The number of neighbours used to select the kernel bandwidth.

      - ##### m_NNSearch

            NearestNeighbourSearch m_NNSearch

        The nearest neighbour search algorithm to use. (Default: weka.core.neighboursearch.LinearNNSearch)

      - ##### m_Train

            Instances m_Train

        The training instances used for classification.

      - ##### m_UseAllK

            boolean m_UseAllK

        True if m_kNN should be set to all instances.

      - ##### m_WeightKernel

            int m_WeightKernel

        The weighting kernel method currently selected.

      - ##### m_ZeroR

            Classifier m_ZeroR

        a ZeroR model in case no model can be built from the data.

- ## Package weka.classifiers.lazy.kstar

  - ### Class weka.classifiers.lazy.kstar.KStarCache

    class KStarCache extends Object implements Serializable
    serialVersionUID:
      -7693632394267140678L

    - #### Serialized Fields

      - ##### m_Cache

            KStarCache.CacheTable m_Cache

        cache table

  - ### Class weka.classifiers.lazy.kstar.KStarCache.CacheTable

    class CacheTable extends Object implements Serializable
    serialVersionUID:
      -8086106452588253423L

    - #### Serialized Fields

      - ##### EPSILON

            double EPSILON

        Accuracy value for equality

      - ##### m_Count

            int m_Count

        The total number of entries in the hash table.

      - ##### m_LoadFactor

            float m_LoadFactor

        The load factor for the hashtable.

      - ##### m_Table

            KStarCache.TableEntry[] m_Table

        The hash table data.

      - ##### m_Threshold

            int m_Threshold

        Rehashes the table when count exceeds this threshold.

  - ### Class weka.classifiers.lazy.kstar.KStarCache.TableEntry

    class TableEntry extends Object implements Serializable
    serialVersionUID:
      4057602386766259138L

    - #### Serialized Fields

      - ##### hash

            int hash

        attribute value hash code

      - ##### key

            double key

        attribute value

      - ##### next

            KStarCache.TableEntry next

        next table entry (separate chaining)

      - ##### pmiss

            double pmiss

        transformation probability to missing value

      - ##### value

            double value

        scale factor or stop parameter

- ## Package weka.classifiers.meta

  - ### Class weka.classifiers.meta.AdaBoostM1

    class AdaBoostM1 extends RandomizableIteratedSingleClassifierEnhancer implements Serializable
    serialVersionUID:
      -1178107808933117974L

    - #### Serialized Fields

      - ##### m_Betas

            double[] m_Betas

        Array for storing the weights for the votes.

      - ##### m_NumClasses

            int m_NumClasses

        The number of classes

      - ##### m_NumIterationsPerformed

            int m_NumIterationsPerformed

        The number of successfully generated base classifiers.

      - ##### m_NumItsThisSession

            int m_NumItsThisSession

        Number of iterations performed in this session of iterating

      - ##### m_RandomInstance

            Random m_RandomInstance

        Random number generator to be used for resampling

      - ##### m_resume

            boolean m_resume

        Whether to allow training to continue at a later point after the initial model is built.

      - ##### m_TrainingData

            Instances m_TrainingData

        The (weighted) training data

      - ##### m_UseResampling

            boolean m_UseResampling

        Use boosting with reweighting?

      - ##### m_WeightThreshold

            int m_WeightThreshold

        Weight Threshold. The percentage of weight mass used in training

      - ##### m_ZeroR

            Classifier m_ZeroR

        a ZeroR model in case no model can be built from the data

  - ### Class weka.classifiers.meta.AdditiveRegression

    class AdditiveRegression extends IteratedSingleClassifierEnhancer implements Serializable
    serialVersionUID:
      -2368937577670527151L

    - #### Serialized Fields

      - ##### m_Classifiers

            ArrayList<Classifier> m_Classifiers

        ArrayList for storing the generated base classifiers. Note: we are hiding the variable from IteratedSingleClassifierEnhancer

      - ##### m_Data

            Instances m_Data

        The working data

      - ##### m_Diff

            double m_Diff

        The improvement in the sum of (absolute or squared) residuals.

      - ##### m_Error

            double m_Error

        The sum of (absolute or squared) residuals.

      - ##### m_InitialPrediction

            double m_InitialPrediction

        The mean or median

      - ##### m_MinimizeAbsoluteError

            boolean m_MinimizeAbsoluteError

        Whether to minimise absolute error instead of squared error.

      - ##### m_numItsPerformed

            int m_numItsPerformed

        Number of iterations performed in this session of iterating

      - ##### m_resume

            boolean m_resume

        Whether to allow training to continue at a later point after the initial model is built.

      - ##### m_shrinkage

            double m_shrinkage

        Shrinkage (Learning rate). Default = no shrinkage.

      - ##### m_SuitableData

            boolean m_SuitableData

        whether we have suitable data or nor (if only mean/mode is used)

  - ### Class weka.classifiers.meta.AttributeSelectedClassifier

    class AttributeSelectedClassifier extends SingleClassifierEnhancer implements Serializable
    serialVersionUID:
      -1151805453487947577L

    - #### Serialized Fields

      - ##### m_AttributeSelection

            AttributeSelection m_AttributeSelection

        The attribute selection object

      - ##### m_Evaluator

            ASEvaluation m_Evaluator

        The attribute evaluator to use

      - ##### m_numAttributesSelected

            double m_numAttributesSelected

        The number of attributes selected by the attribute selection phase

      - ##### m_numClasses

            int m_numClasses

        The number of class vals in the training data (1 if class is numeric)

      - ##### m_ReducedHeader

            Instances m_ReducedHeader

        The header of the dimensionally reduced data

      - ##### m_Search

            ASSearch m_Search

        The search method to use

      - ##### m_selectionTime

            double m_selectionTime

        The time taken to select attributes in milliseconds

      - ##### m_totalTime

            double m_totalTime

        The time taken to select attributes AND build the classifier

  - ### Class weka.classifiers.meta.Bagging

    class Bagging extends RandomizableParallelIteratedSingleClassifierEnhancer implements Serializable
    serialVersionUID:
      -115879962237199703L

    - #### Serialized Fields

      - ##### m_BagSizePercent

            int m_BagSizePercent

        The size of each bag sample, as a percentage of the training size

      - ##### m_CalcOutOfBag

            boolean m_CalcOutOfBag

        Whether to calculate the out of bag error

      - ##### m_classifiersCache

            List<Classifier> m_classifiersCache

      - ##### m_data

            Instances m_data

        Reference to the training data

      - ##### m_inBag

            boolean[][] m_inBag

        Used to indicate whether an instance is in a bag or not

      - ##### m_Numeric

            boolean m_Numeric

        Whether class is numeric.

      - ##### m_OutOfBagEvaluationObject

            Evaluation m_OutOfBagEvaluationObject

        The evaluation object holding the out of bag error, etc.

      - ##### m_OutputOutOfBagComplexityStatistics

            boolean m_OutputOutOfBagComplexityStatistics

        Whether to output complexity-based statistics when OOB-evaluation is performed.

      - ##### m_printClassifiers

            boolean m_printClassifiers

        Whether to print individual ensemble members in output.

      - ##### m_random

            Random m_random

        Random number generator

      - ##### m_RepresentUsingWeights

            boolean m_RepresentUsingWeights

        Whether to represent copies of instances using weights rather than explicitly

      - ##### m_StoreOutOfBagPredictions

            boolean m_StoreOutOfBagPredictions

        Whether to store the out of bag predictions in the evaluation object.

  - ### Class weka.classifiers.meta.ClassificationViaRegression

    class ClassificationViaRegression extends SingleClassifierEnhancer implements Serializable
    serialVersionUID:
      4500023123618669859L

    - #### Serialized Fields

      - ##### m_ClassFilters

            MakeIndicator[] m_ClassFilters

        The filters used to transform the class.

      - ##### m_Classifiers

            Classifier[] m_Classifiers

        The classifiers. (One for each class.)

  - ### Class weka.classifiers.meta.CostSensitiveClassifier

    class CostSensitiveClassifier extends RandomizableSingleClassifierEnhancer implements Serializable
    serialVersionUID:
      -110658209263002404L

    - #### Serialized Fields

      - ##### m_CostFile

            String m_CostFile

        The name of the cost file, for command line options

      - ##### m_CostMatrix

            CostMatrix m_CostMatrix

        The cost matrix

      - ##### m_MatrixSource

            int m_MatrixSource

        Indicates the current cost matrix source

      - ##### m_MinimizeExpectedCost

            boolean m_MinimizeExpectedCost

        True if the costs should be used by selecting the minimum expected cost (false means weight training data by the costs)

      - ##### m_OnDemandDirectory

            File m_OnDemandDirectory

        The directory used when loading cost files on demand, null indicates current directory

  - ### Class weka.classifiers.meta.CVParameterSelection

    class CVParameterSelection extends RandomizableSingleClassifierEnhancer implements Serializable
    serialVersionUID:
      -6529603380876641265L

    - #### Serialized Fields

      - ##### m_BestClassifierOptions

            String[] m_BestClassifierOptions

        The set of all classifier options as determined by cross-validation

      - ##### m_BestPerformance

            double m_BestPerformance

        The cross-validated performance of the best options

      - ##### m_ClassifierOptions

            String[] m_ClassifierOptions

        The base classifier options (not including those being set by cross-validation)

      - ##### m_CVParams

            Vector<weka.classifiers.meta.CVParameterSelection.CVParameter> m_CVParams

        The set of parameters to cross-validate over

      - ##### m_InitOptions

            String[] m_InitOptions

        The set of all options at initialization time. So that getOptions can return this.

      - ##### m_NumAttributes

            int m_NumAttributes

        The number of attributes in the data

      - ##### m_NumFolds

            int m_NumFolds

        The number of folds used in cross-validation

      - ##### m_TrainFoldSize

            int m_TrainFoldSize

        The number of instances in a training fold

  - ### Class weka.classifiers.meta.CVParameterSelection.CVParameter

    class CVParameter extends Object implements Serializable
    serialVersionUID:
      -4668812017709421953L

    - #### Serialized Fields

      - ##### m_AddAtEnd

            boolean m_AddAtEnd

        True if the parameter should be added at the end of the argument list

      - ##### m_Lower

            double m_Lower

        Lower bound for the CV search

      - ##### m_ParamChar

            String m_ParamChar

        Char used to identify the option of interest

      - ##### m_ParamValue

            double m_ParamValue

        The parameter value with the best performance

      - ##### m_RoundParam

            boolean m_RoundParam

        True if the parameter should be rounded to an integer

      - ##### m_Steps

            double m_Steps

        Number of steps during the search

      - ##### m_Upper

            double m_Upper

        Upper bound for the CV search

  - ### Class weka.classifiers.meta.FilteredClassifier

    class FilteredClassifier extends RandomizableSingleClassifierEnhancer implements Serializable
    serialVersionUID:
      -4523450618538717400L

    - #### Serialized Fields

      - ##### m_DoNotCheckForModifiedClassAttribute

            boolean m_DoNotCheckForModifiedClassAttribute

        Flag that can be set to true if class attribute is not to be checked for modifications by the filer.

      - ##### m_Filter

            Filter m_Filter

        The filter

      - ##### m_FilteredInstances

            Instances m_FilteredInstances

        The instance structure of the filtered instances

      - ##### m_ReorderFiltered

            Reorder m_ReorderFiltered

      - ##### m_ReorderOriginal

            Reorder m_ReorderOriginal

        If the attributes are resampled, we store the filter for this

  - ### Class weka.classifiers.meta.IterativeClassifierOptimizer

    class IterativeClassifierOptimizer extends RandomizableClassifier implements Serializable
    serialVersionUID:
      -3665485256313525864L

    - #### Serialized Fields

      - ##### m_bestNumIts

            int m_bestNumIts

        The best number of iterations identified.

      - ##### m_bestResult

            double m_bestResult

        The best value found for the criterion to be optimized.

      - ##### m_classValueIndex

            int m_classValueIndex

        The class value index to use with information retrieval type metrics. < 0 indicates to use the class weighted average version of the metric".

      - ##### m_evalMetric

            String m_evalMetric

        The evaluation metric to use

      - ##### m_IterativeClassifier

            IterativeClassifier m_IterativeClassifier

        The base classifier to use

      - ##### m_lookAheadIterations

            int m_lookAheadIterations

        The number of iterations to look ahead for to find a better optimum.

      - ##### m_NumFolds

            int m_NumFolds

        The number of folds for the cross-validation.

      - ##### m_NumRuns

            int m_NumRuns

        The number of runs for the cross-validation.

      - ##### m_numThreads

            int m_numThreads

        The number of threads to use for parallel building of classifiers.

      - ##### m_poolSize

            int m_poolSize

        The size of the thread pool.

      - ##### m_preserveOrderInPercentageSplitEvaluation

            boolean m_preserveOrderInPercentageSplitEvaluation

        Whether to preserve order when a percentage split evaluation is performed.

      - ##### m_splitPercentage

            double m_splitPercentage

        The percentage of data to be used for training (if 0, k-fold cross-validation is used).

      - ##### m_StepSize

            int m_StepSize

        The steps size determining when evaluations happen.

      - ##### m_thresholds

            double[] m_thresholds

        The thresholds to be used for classification, if the metric implements ThresholdProducingMetric.

      - ##### m_UseAverage

            boolean m_UseAverage

        Whether to use average.

  - ### Class weka.classifiers.meta.LogitBoost

    class LogitBoost extends RandomizableIteratedSingleClassifierEnhancer implements Serializable
    serialVersionUID:
      -1105660358715833753L

    - #### Serialized Fields

      - ##### m_ClassAttribute

            Attribute m_ClassAttribute

        The actual class attribute (for getting class names)

      - ##### m_Classifiers

            ArrayList<Classifier[]> m_Classifiers

        ArrayList for storing the generated base classifiers. Note: we are hiding the variable from IteratedSingleClassifierEnhancer

      - ##### m_data

            Instances m_data

        The training data.

      - ##### m_InitialFs

            double[] m_InitialFs

        The initial F scores (0 by default)

      - ##### m_logLikelihood

            double m_logLikelihood

        The current loglikelihood.

      - ##### m_NumClasses

            int m_NumClasses

        The number of classes

      - ##### m_NumericClassData

            Instances m_NumericClassData

        Dummy dataset with a numeric class

      - ##### m_NumGenerated

            int m_NumGenerated

        The number of successfully generated base classifiers.

      - ##### m_NumItsPerformed

            int m_NumItsPerformed

        Number of iterations performed in this session of iterating

      - ##### m_numThreads

            int m_numThreads

        The number of threads to use at prediction time in batch prediction.

      - ##### m_Offset

            double m_Offset

        The value by which the actual target value for the true class is offset.

      - ##### m_poolSize

            int m_poolSize

        The size of the thread pool.

      - ##### m_Precision

            double m_Precision

        The threshold on the improvement of the likelihood

      - ##### m_probs

            double[][] m_probs

        The probabilities used during the training process.

      - ##### m_RandomInstance

            Random m_RandomInstance

        The random number generator used

      - ##### m_resume

            boolean m_resume

        Whether to allow training to continue at a later point after the initial model is built.

      - ##### m_Shrinkage

            double m_Shrinkage

        The value of the shrinkage parameter

      - ##### m_sumOfWeights

            double m_sumOfWeights

        The total weight of the data.

      - ##### m_trainFs

            double[][] m_trainFs

        The F scores used during the training process.

      - ##### m_trainYs

            double[][] m_trainYs

        The y values used during the training process.

      - ##### m_UseEstimatedPriors

            boolean m_UseEstimatedPriors

        Whether to start with class priors estimated from the training data

      - ##### m_UseResampling

            boolean m_UseResampling

        Use boosting with reweighting?

      - ##### m_WeightThreshold

            int m_WeightThreshold

        Weight thresholding. The percentage of weight mass used in training

      - ##### m_ZeroR

            Classifier m_ZeroR

        A ZeroR model in case no model can be built from the data

      - ##### m_zMax

            double m_zMax

        The Z max value to use

  - ### Class weka.classifiers.meta.MultiClassClassifier

    class MultiClassClassifier extends RandomizableSingleClassifierEnhancer implements Serializable
    serialVersionUID:
      -3879602011542849141L

    - #### Serialized Fields

      - ##### m_ClassAttribute

            Attribute m_ClassAttribute

        Internal copy of the class attribute for output purposes

      - ##### m_ClassFilters

            Filter[] m_ClassFilters

        The filters used to transform the class.

      - ##### m_Classifiers

            Classifier[] m_Classifiers

        The classifiers.

      - ##### m_logLossDecoding

            boolean m_logLossDecoding

        True if log loss decoding is to be used for random and exhaustive codes.

      - ##### m_Method

            int m_Method

        The multiclass method to use

      - ##### m_pairwiseCoupling

            boolean m_pairwiseCoupling

        Use pairwise coupling with 1-vs-1

      - ##### m_RandomWidthFactor

            double m_RandomWidthFactor

        The multiplier when generating random codes. Will generate numClasses * m_RandomWidthFactor codes

      - ##### m_SumOfWeights

            double[] m_SumOfWeights

        Needed for pairwise coupling

      - ##### m_TwoClassDataset

            Instances m_TwoClassDataset

        A transformed dataset header used by the 1-against-1 method

      - ##### m_ZeroR

            ZeroR m_ZeroR

        ZeroR classifier for when all base classifier return zero probability.

  - ### Class weka.classifiers.meta.MultiClassClassifierUpdateable

    class MultiClassClassifierUpdateable extends MultiClassClassifier implements Serializable
    serialVersionUID:
      -1619685269774366430L

  - ### Class weka.classifiers.meta.MultiScheme

    class MultiScheme extends RandomizableMultipleClassifiersCombiner implements Serializable
    serialVersionUID:
      5710744346128957520L

    - #### Serialized Fields

      - ##### m_Classifier

            Classifier m_Classifier

        The classifier that had the best performance on training data.

      - ##### m_ClassifierIndex

            int m_ClassifierIndex

        The index into the vector for the selected scheme

      - ##### m_NumXValFolds

            int m_NumXValFolds

        Number of folds to use for cross validation (0 means use training error for selection)

  - ### Class weka.classifiers.meta.RandomCommittee

    class RandomCommittee extends RandomizableParallelIteratedSingleClassifierEnhancer implements Serializable
    serialVersionUID:
      -9204394360557300093L

    - #### Serialized Fields

      - ##### m_data

            Instances m_data

        training data

  - ### Class weka.classifiers.meta.RandomizableFilteredClassifier

    class RandomizableFilteredClassifier extends FilteredClassifier implements Serializable
    serialVersionUID:
      -4523466618555717333L

  - ### Class weka.classifiers.meta.RandomSubSpace

    class RandomSubSpace extends RandomizableParallelIteratedSingleClassifierEnhancer implements Serializable
    serialVersionUID:
      1278172513912424947L

    - #### Serialized Fields

      - ##### m_data

            Instances m_data

        Training data

      - ##### m_SubSpaceSize

            double m_SubSpaceSize

        The size of each bag sample, as a percentage of the training size

      - ##### m_ZeroR

            Classifier m_ZeroR

        a ZeroR model in case no model can be built from the data

  - ### Class weka.classifiers.meta.RegressionByDiscretization

    class RegressionByDiscretization extends SingleClassifierEnhancer implements Serializable
    serialVersionUID:
      5066426153134050378L

    - #### Serialized Fields

      - ##### m_ClassCounts

            int[] m_ClassCounts

        The class counts for each Discretized class interval.

      - ##### m_ClassMeans

            double[] m_ClassMeans

        The mean values for each Discretized class interval.

      - ##### m_DeleteEmptyBins

            boolean m_DeleteEmptyBins

        Whether to delete empty intervals.

      - ##### m_DiscretizedHeader

            Instances m_DiscretizedHeader

        Header of discretized data.

      - ##### m_Discretizer

            Discretize m_Discretizer

        The discretization filter.

      - ##### m_Estimator

            UnivariateDensityEstimator m_Estimator

        Which estimator to use (default: histogram)

      - ##### m_MinimizeAbsoluteError

            boolean m_MinimizeAbsoluteError

        Whether to minimize absolute error, rather than squared error.

      - ##### m_NewTargetValues

            int[] m_NewTargetValues

        The converted target values in the training data

      - ##### m_NumBins

            int m_NumBins

        The number of discretization intervals.

      - ##### m_OldIndexToNewIndex

            int[] m_OldIndexToNewIndex

        Mapping to convert indices in case empty bins are deleted.

      - ##### m_OriginalTargetValues

            double[] m_OriginalTargetValues

        The original target values in the training data

      - ##### m_UseEqualFrequency

            boolean m_UseEqualFrequency

        Use equal-frequency binning

  - ### Class weka.classifiers.meta.Stacking

    class Stacking extends RandomizableParallelMultipleClassifiersCombiner implements Serializable
    serialVersionUID:
      5134738557155845452L

    - #### Serialized Fields

      - ##### m_BaseFormat

            Instances m_BaseFormat

        Format for base data

      - ##### m_MetaClassifier

            Classifier m_MetaClassifier

        The meta classifier

      - ##### m_MetaFormat

            Instances m_MetaFormat

        Format for meta data

      - ##### m_NumFolds

            int m_NumFolds

        Set the number of folds for the cross-validation

  - ### Class weka.classifiers.meta.Vote

    class Vote extends RandomizableMultipleClassifiersCombiner implements Serializable
    serialVersionUID:
      -637891196294399624L

    - #### Serialized Fields

      - ##### m_classifiersToLoad

            List<String> m_classifiersToLoad

        List of file paths to serialized models to load

      - ##### m_CombinationRule

            int m_CombinationRule

        Combination Rule variable

      - ##### m_dontPrintModels

            boolean m_dontPrintModels

        Print the individual models in the output

      - ##### m_preBuiltClassifiers

            List<Classifier> m_preBuiltClassifiers

        List of de-serialized pre-built classifiers to include in the ensemble

      - ##### m_structure

            Instances m_structure

        Structure of the training data

  - ### Class weka.classifiers.meta.WeightedInstancesHandlerWrapper

    class WeightedInstancesHandlerWrapper extends RandomizableSingleClassifierEnhancer implements Serializable
    serialVersionUID:
      2980789213434466135L

    - #### Serialized Fields

      - ##### m_ForceResampleWithWeights

            boolean m_ForceResampleWithWeights

        whether to force resampling with weights.

- ## Package weka.classifiers.misc

  - ### Class weka.classifiers.misc.InputMappedClassifier

    class InputMappedClassifier extends SingleClassifierEnhancer implements Serializable
    serialVersionUID:
      4901630631723287761L

    - #### Serialized Fields

      - ##### m_ignoreCase

            boolean m_ignoreCase

        Ignore case when matching attribute names and nominal values?

      - ##### m_initialTestStructureKnown

            boolean m_initialTestStructureKnown

        If true, then a call to buildClassifier() will not overwrite any test structure that has been recorded with the current training structure. This is useful for getting a correct mapping report output in toString() after buildClassifier has been called and before any test instance has been seen. Test structure and mapping will get reset if a test instance is received whose structure does not match the recorded test structure.

      - ##### m_modelHeader

            Instances m_modelHeader

        The instances structure used to train the classifier with

      - ##### m_modelPath

            String m_modelPath

        The path to the serialized model to use (if any)

      - ##### m_suppressMappingReport

            boolean m_suppressMappingReport

        Dont output mapping report if set to true

      - ##### m_trim

            boolean m_trim

        Trim white space from both ends of attribute names and nominal values?

      - ##### m_vals

            double[] m_vals

        Holds values for instances constructed for prediction

  - ### Class weka.classifiers.misc.SerializedClassifier

    class SerializedClassifier extends AbstractClassifier implements Serializable
    serialVersionUID:
      4599593909947628642L

    - #### Serialized Fields

      - ##### m_ModelFile

            File m_ModelFile

        the file where the serialized model is stored

- ## Package weka.classifiers.pmml.consumer

  - ### Class weka.classifiers.pmml.consumer.GeneralRegression

    class GeneralRegression extends PMMLClassifier implements Serializable
    serialVersionUID:
      2583880411828388959L

    - #### Serialized Fields

      - ##### m_algorithmName

            String m_algorithmName

      - ##### m_covariateList

            ArrayList<weka.classifiers.pmml.consumer.GeneralRegression.Predictor> m_covariateList

      - ##### m_cumulativeLinkFunction

            weka.classifiers.pmml.consumer.GeneralRegression.CumulativeLinkFunction m_cumulativeLinkFunction

      - ##### m_distParameter

            double m_distParameter

      - ##### m_distribution

            weka.classifiers.pmml.consumer.GeneralRegression.Distribution m_distribution

      - ##### m_factorList

            ArrayList<weka.classifiers.pmml.consumer.GeneralRegression.Predictor> m_factorList

      - ##### m_functionType

            int m_functionType

      - ##### m_linkFunction

            weka.classifiers.pmml.consumer.GeneralRegression.LinkFunction m_linkFunction

      - ##### m_linkParameter

            double m_linkParameter

      - ##### m_modelName

            String m_modelName

      - ##### m_modelType

            weka.classifiers.pmml.consumer.GeneralRegression.ModelType m_modelType

      - ##### m_offsetValue

            double m_offsetValue

      - ##### m_offsetVariable

            String m_offsetVariable

      - ##### m_parameterList

            ArrayList<weka.classifiers.pmml.consumer.GeneralRegression.Parameter> m_parameterList

      - ##### m_paramMatrix

            weka.classifiers.pmml.consumer.GeneralRegression.PCell[][] m_paramMatrix

      - ##### m_ppMatrix

            weka.classifiers.pmml.consumer.GeneralRegression.PPCell[][] m_ppMatrix

      - ##### m_trialsValue

            double m_trialsValue

      - ##### m_trialsVariable

            String m_trialsVariable

  - ### Class weka.classifiers.pmml.consumer.NeuralNetwork

    class NeuralNetwork extends PMMLClassifier implements Serializable
    serialVersionUID:
      -4545904813133921249L

    - #### Serialized Fields

      - ##### m_activationFunction

            weka.classifiers.pmml.consumer.NeuralNetwork.ActivationFunction m_activationFunction

        The activation function to use

      - ##### m_altitude

            double m_altitude

        Altitude for radial basis

      - ##### m_functionType

            weka.classifiers.pmml.consumer.NeuralNetwork.MiningFunction m_functionType

        The mining function

      - ##### m_inputMap

            HashMap<String,Double> m_inputMap

        A map for storing network input values (computed from an incoming instance)

      - ##### m_inputs

            weka.classifiers.pmml.consumer.NeuralNetwork.NeuralInput[] m_inputs

        The inputs to the network

      - ##### m_layers

            weka.classifiers.pmml.consumer.NeuralNetwork.NeuralLayer[] m_layers

        The hidden layers in the network

      - ##### m_normalizationMethod

            weka.classifiers.pmml.consumer.NeuralNetwork.Normalization m_normalizationMethod

        The normalization method

      - ##### m_numberOfInputs

            int m_numberOfInputs

        The number of inputs to the network

      - ##### m_numberOfLayers

            int m_numberOfLayers

        Number of hidden layers in the network

      - ##### m_outputs

            weka.classifiers.pmml.consumer.NeuralNetwork.NeuralOutputs m_outputs

        The outputs of the network

      - ##### m_threshold

            double m_threshold

        Threshold activation

      - ##### m_width

            double m_width

        Width for radial basis

  - ### Class weka.classifiers.pmml.consumer.PMMLClassifier

    class PMMLClassifier extends AbstractClassifier implements Serializable
    serialVersionUID:
      -5371600590320702971L

    - #### Serialized Fields

      - ##### m_creatorApplication

            String m_creatorApplication

        Creator application

      - ##### m_dataDictionary

            Instances m_dataDictionary

        The data dictionary

      - ##### m_log

            Logger m_log

        Logger

      - ##### m_miningSchema

            MiningSchema m_miningSchema

        The fields and meta data used by the model

      - ##### m_pmmlVersion

            String m_pmmlVersion

        PMML version

  - ### Class weka.classifiers.pmml.consumer.Regression

    class Regression extends PMMLClassifier implements Serializable
    serialVersionUID:
      -5551125528409488634L

    - #### Serialized Fields

      - ##### m_algorithmName

            String m_algorithmName

        Description of the algorithm

      - ##### m_normalizationMethod

            weka.classifiers.pmml.consumer.Regression.Normalization m_normalizationMethod

        The normalization to use

      - ##### m_regressionTables

            weka.classifiers.pmml.consumer.Regression.RegressionTable[] m_regressionTables

        The regression tables for this regression

  - ### Class weka.classifiers.pmml.consumer.Regression.RegressionTable.CategoricalPredictor

    class CategoricalPredictor extends weka.classifiers.pmml.consumer.Regression.RegressionTable.Predictor implements Serializable
    serialVersionUID:
      3077920125549906819L

    - #### Serialized Fields

      - ##### m_valueIndex

            int m_valueIndex

        The index of the attribute value for this predictor

      - ##### m_valueName

            String m_valueName

        The attribute value for this predictor

  - ### Class weka.classifiers.pmml.consumer.Regression.RegressionTable.NumericPredictor

    class NumericPredictor extends weka.classifiers.pmml.consumer.Regression.RegressionTable.Predictor implements Serializable
    serialVersionUID:
      -4335075205696648273L

    - #### Serialized Fields

      - ##### m_exponent

            double m_exponent

        The exponent

  - ### Class weka.classifiers.pmml.consumer.Regression.RegressionTable.PredictorTerm

    class PredictorTerm extends Object implements Serializable
    serialVersionUID:
      5493100145890252757L

    - #### Serialized Fields

      - ##### m_coefficient

            double m_coefficient

        The coefficient for this predictor term

      - ##### m_fieldNames

            String[] m_fieldNames

        The names of the terms (attributes) to be multiplied

      - ##### m_indexes

            int[] m_indexes

        the indexes of the terms to be multiplied

  - ### Class weka.classifiers.pmml.consumer.RuleSetModel

    class RuleSetModel extends PMMLClassifier implements Serializable
    serialVersionUID:
      1993161168811020547L

    - #### Serialized Fields

      - ##### m_algorithmName

            String m_algorithmName

        The algorithm name (if defined)

      - ##### m_functionType

            weka.classifiers.pmml.consumer.TreeModel.MiningFunction m_functionType

        The mining function

      - ##### m_modelName

            String m_modelName

        The model name (if defined)

      - ##### m_ruleSet

            weka.classifiers.pmml.consumer.RuleSetModel.RuleSet m_ruleSet

        The set of rules

  - ### Class weka.classifiers.pmml.consumer.SupportVectorMachineModel

    class SupportVectorMachineModel extends PMMLClassifier implements Serializable
    serialVersionUID:
      6225095165118374296L

    - #### Serialized Fields

      - ##### m_algorithmName

            String m_algorithmName

        The algorithm name (if defined)

      - ##### m_alternateBinaryTargetCategory

            int m_alternateBinaryTargetCategory

        The other class index (in the case of a single binary SVM - PMML 3.2).

      - ##### m_classificationMethod

            weka.classifiers.pmml.consumer.SupportVectorMachineModel.classificationMethod m_classificationMethod

        The classification method (PMML 4.0)

      - ##### m_functionType

            weka.classifiers.pmml.consumer.NeuralNetwork.MiningFunction m_functionType

        The mining function

      - ##### m_kernel

            weka.classifiers.pmml.consumer.SupportVectorMachineModel.Kernel m_kernel

        The kernel function to use

      - ##### m_machines

            List<weka.classifiers.pmml.consumer.SupportVectorMachineModel.SupportVectorMachine> m_machines

        The individual binary SVMs

      - ##### m_modelName

            String m_modelName

        The model name (if defined)

      - ##### m_svmRepresentation

            weka.classifiers.pmml.consumer.SupportVectorMachineModel.SVM_representation m_svmRepresentation

        Do we have support vectors, or just attribute coefficients for a linear machine?

      - ##### m_threshold

            double m_threshold

        PMML 4.0 threshold value

      - ##### m_vectorDictionary

            VectorDictionary m_vectorDictionary

        The dictionary of support vectors

  - ### Class weka.classifiers.pmml.consumer.TreeModel

    class TreeModel extends PMMLClassifier implements Serializable
    serialVersionUID:
      -2065158088298753129L

    - #### Serialized Fields

      - ##### m_functionType

            weka.classifiers.pmml.consumer.TreeModel.MiningFunction m_functionType

        The mining function

      - ##### m_missingValuePenalty

            double m_missingValuePenalty

        The missing value penalty (if defined). We don't actually make use of this since we always return full probability distributions.

      - ##### m_missingValueStrategy

            weka.classifiers.pmml.consumer.TreeModel.MissingValueStrategy m_missingValueStrategy

        The missing value strategy

      - ##### m_noTrueChildStrategy

            weka.classifiers.pmml.consumer.TreeModel.NoTrueChildStrategy m_noTrueChildStrategy

        The no true child strategy to use

      - ##### m_root

            weka.classifiers.pmml.consumer.TreeModel.TreeNode m_root

        The root of the tree

      - ##### m_splitCharacteristic

            weka.classifiers.pmml.consumer.TreeModel.SplitCharacteristic m_splitCharacteristic

        The splitting type

- ## Package weka.classifiers.rules

  - ### Class weka.classifiers.rules.DecisionTable

    class DecisionTable extends AbstractClassifier implements Serializable
    serialVersionUID:
      2888557078165701326L

    - #### Serialized Fields

      - ##### m_classIsNominal

            boolean m_classIsNominal

        Class is nominal

      - ##### m_classPriorCounts

            double[] m_classPriorCounts

        The class priors to use when there is no match in the table

      - ##### m_classPriors

            double[] m_classPriors

      - ##### m_CVFolds

            int m_CVFolds

        Number of folds for cross validating feature sets

      - ##### m_decisionFeatures

            int[] m_decisionFeatures

        Holds the final feature set

      - ##### m_delTransform

            Remove m_delTransform

        Filter used to remove columns discarded by feature selection

      - ##### m_displayRules

            boolean m_displayRules

        Display Rules

      - ##### m_disTransform

            Filter m_disTransform

        Discretization filter

      - ##### m_dtInstances

            Instances m_dtInstances

        Holds the final feature selected set of instances

      - ##### m_entries

            Hashtable<DecisionTableHashKey,double[]> m_entries

        The hashtable used to hold training instances

      - ##### m_evaluation

            Evaluation m_evaluation

        The evaluation object used to evaluate subsets

      - ##### m_evaluationMeasure

            int m_evaluationMeasure

      - ##### m_evaluator

            ASEvaluation m_evaluator

        Our own internal evaluator

      - ##### m_ibk

            IBk m_ibk

        IB1 used to classify non matching instances rather than majority class

      - ##### m_majority

            double m_majority

        Holds the majority class

      - ##### m_numAttributes

            int m_numAttributes

        The number of attributes in the dataset

      - ##### m_numInstances

            int m_numInstances

        The number of instances in the dataset

      - ##### m_rr

            Random m_rr

        Random numbers for use in cross validation

      - ##### m_saveMemory

            boolean m_saveMemory

      - ##### m_search

            ASSearch m_search

        The search method to use

      - ##### m_theInstances

            Instances m_theInstances

        Holds the original training instances

      - ##### m_useIBk

            boolean m_useIBk

        Use the IBk classifier rather than majority class

  - ### Class weka.classifiers.rules.DecisionTableHashKey

    class DecisionTableHashKey extends Object implements Serializable
    serialVersionUID:
      5674163500154964602L

    - #### Serialized Fields

      - ##### attributes

            double[] attributes

        Array of attribute values for an instance

      - ##### key

            int key

        The key

      - ##### missing

            boolean[] missing

        True for an index if the corresponding attribute value is missing.

  - ### Class weka.classifiers.rules.JRip

    class JRip extends AbstractClassifier implements Serializable
    serialVersionUID:
      -6589312996832147161L

    - #### Serialized Fields

      - ##### m_CheckErr

            boolean m_CheckErr

        Whether check the error rate >= 0.5 in stopping criteria

      - ##### m_Class

            Attribute m_Class

        The class attribute of the data

      - ##### m_Debug

            boolean m_Debug

        Whether in a debug mode

      - ##### m_Distributions

            ArrayList<double[]> m_Distributions

        The predicted class distribution

      - ##### m_Filter

            Filter m_Filter

        The filter used to randomize the class order

      - ##### m_Folds

            int m_Folds

        The number of folds to split data into Grow and Prune for IREP

      - ##### m_MinNo

            double m_MinNo

        The minimal number of instance weights within a split

      - ##### m_Optimizations

            int m_Optimizations

        Runs of optimizations

      - ##### m_Random

            Random m_Random

        Random object used in this class

      - ##### m_Ruleset

            ArrayList<Rule> m_Ruleset

        The ruleset

      - ##### m_RulesetStats

            ArrayList<RuleStats> m_RulesetStats

        The RuleStats for the ruleset of each class value

      - ##### m_Seed

            long m_Seed

        The seed to perform randomization

      - ##### m_Total

            double m_Total

        # of all the possible conditions in a rule

      - ##### m_UsePruning

            boolean m_UsePruning

        Whether use pruning, i.e. the data is clean or not

  - ### Class weka.classifiers.rules.JRip.Antd

    class Antd extends Object implements Serializable
    serialVersionUID:
      -8929754772994154334L

    - #### Serialized Fields

      - ##### accu

            double accu

        The accurate data for this antecedent in the growing data

      - ##### accuRate

            double accuRate

        The accurate rate of this antecedent test on the growing data

      - ##### att

            Attribute att

        The attribute of the antecedent

      - ##### cover

            double cover

        The coverage of this antecedent in the growing data

      - ##### maxInfoGain

            double maxInfoGain

        The maximum infoGain achieved by this antecedent test in the growing data

      - ##### value

            double value

        The attribute value of the antecedent. For numeric attribute, value is either 0(1st bag) or 1(2nd bag)

  - ### Class weka.classifiers.rules.JRip.NominalAntd

    class NominalAntd extends JRip.Antd implements Serializable
    serialVersionUID:
      -9102297038837585135L

    - #### Serialized Fields

      - ##### accurate

            double[] accurate

      - ##### coverage

            double[] coverage

  - ### Class weka.classifiers.rules.JRip.NumericAntd

    class NumericAntd extends JRip.Antd implements Serializable
    serialVersionUID:
      5699457269983735442L

    - #### Serialized Fields

      - ##### splitPoint

            double splitPoint

        The split point for this numeric antecedent

  - ### Class weka.classifiers.rules.JRip.RipperRule

    class RipperRule extends Rule implements Serializable
    serialVersionUID:
      -2410020717305262952L

    - #### Serialized Fields

      - ##### m_Antds

            ArrayList<JRip.Antd> m_Antds

        The vector of antecedents of this rule

      - ##### m_Consequent

            double m_Consequent

        The internal representation of the class label to be predicted

  - ### Class weka.classifiers.rules.M5Rules

    class M5Rules extends M5Base implements Serializable
    serialVersionUID:
      -1746114858746563180L

  - ### Class weka.classifiers.rules.OneR

    class OneR extends AbstractClassifier implements Serializable
    serialVersionUID:
      -3459427003147861443L

    - #### Serialized Fields

      - ##### m_minBucketSize

            int m_minBucketSize

        The minimum bucket size

      - ##### m_rule

            weka.classifiers.rules.OneR.OneRRule m_rule

        A 1-R rule

      - ##### m_ZeroR

            Classifier m_ZeroR

        a ZeroR model in case no model can be built from the data

  - ### Class weka.classifiers.rules.PART

    class PART extends AbstractClassifier implements Serializable
    serialVersionUID:
      8121455039782598361L

    - #### Serialized Fields

      - ##### m_binarySplits

            boolean m_binarySplits

        Binary splits on nominal attributes?

      - ##### m_CF

            float m_CF

        Confidence level

      - ##### m_doNotMakeSplitPointActualValue

            boolean m_doNotMakeSplitPointActualValue

        Do not relocate split point to actual data value

      - ##### m_minNumObj

            int m_minNumObj

        Minimum number of objects

      - ##### m_numFolds

            int m_numFolds

        Number of folds for reduced error pruning.

      - ##### m_reducedErrorPruning

            boolean m_reducedErrorPruning

        Use reduced error pruning?

      - ##### m_root

            MakeDecList m_root

        The decision list

      - ##### m_Seed

            int m_Seed

        The seed for random number generation.

      - ##### m_unpruned

            boolean m_unpruned

        Generate unpruned list?

      - ##### m_useMDLcorrection

            boolean m_useMDLcorrection

        Use MDL correction?

  - ### Class weka.classifiers.rules.Rule

    class Rule extends Object implements Serializable
    serialVersionUID:
      8815687740470471229L

  - ### Class weka.classifiers.rules.RuleStats

    class RuleStats extends Object implements Serializable
    serialVersionUID:
      -5708153367675298624L

    - #### Serialized Fields

      - ##### m_Data

            Instances m_Data

        The data on which the stats calculation is based

      - ##### m_Distributions

            ArrayList<double[]> m_Distributions

        The class distributions predicted by each rule

      - ##### m_Filtered

            ArrayList<Instances[]> m_Filtered

        The set of instances filtered by the ruleset

      - ##### m_Ruleset

            ArrayList<Rule> m_Ruleset

        The specific ruleset in question

      - ##### m_SimpleStats

            ArrayList<double[]> m_SimpleStats

        The simple stats of each rule

      - ##### m_Total

            double m_Total

        The total number of possible conditions that could appear in a rule

      - ##### MDL_THEORY_WEIGHT

            double MDL_THEORY_WEIGHT

        The theory weight in the MDL calculation

  - ### Class weka.classifiers.rules.ZeroR

    class ZeroR extends AbstractClassifier implements Serializable
    serialVersionUID:
      48055541465867954L

    - #### Serialized Fields

      - ##### m_Class

            Attribute m_Class

        The class attribute.

      - ##### m_ClassValue

            double m_ClassValue

        The class value 0R predicts.

      - ##### m_Counts

            double[] m_Counts

        The number of instances in each class (null if class numeric).

- ## Package weka.classifiers.rules.part

  - ### Class weka.classifiers.rules.part.C45PruneableDecList

    class C45PruneableDecList extends ClassifierDecList implements Serializable
    serialVersionUID:
      -2757684345218324559L

    - #### Serialized Fields

      - ##### CF

            double CF

        CF

  - ### Class weka.classifiers.rules.part.ClassifierDecList

    class ClassifierDecList extends Object implements Serializable
    serialVersionUID:
      7284358349711992497L

    - #### Serialized Fields

      - ##### indeX

            int indeX

        Which son to expand?

      - ##### m_isEmpty

            boolean m_isEmpty

        True if node is empty.

      - ##### m_isLeaf

            boolean m_isLeaf

        True if node is leaf.

      - ##### m_localModel

            ClassifierSplitModel m_localModel

        Local model at node.

      - ##### m_minNumObj

            int m_minNumObj

        Minimum number of objects

      - ##### m_sons

            ClassifierDecList[] m_sons

        References to sons.

      - ##### m_test

            Distribution m_test

        The pruning instances.

      - ##### m_toSelectModel

            ModelSelection m_toSelectModel

        The model selection method.

      - ##### m_train

            Instances m_train

        The training instances.

  - ### Class weka.classifiers.rules.part.MakeDecList

    class MakeDecList extends Object implements Serializable
    serialVersionUID:
      -1427481323245079123L

    - #### Serialized Fields

      - ##### CF

            double CF

        The confidence for C45-type pruning.

      - ##### m_seed

            int m_seed

        The seed for random number generation.

      - ##### minNumObj

            int minNumObj

        Minimum number of objects

      - ##### numSetS

            int numSetS

        How many subsets of equal size? One used for pruning, the rest for training.

      - ##### reducedErrorPruning

            boolean reducedErrorPruning

        Use reduced error pruning?

      - ##### theRules

            Vector<ClassifierDecList> theRules

        Vector storing the rules.

      - ##### toSelectModeL

            ModelSelection toSelectModeL

        The model selection method.

      - ##### unpruned

            boolean unpruned

        Generated unpruned list?

  - ### Class weka.classifiers.rules.part.PruneableDecList

    class PruneableDecList extends ClassifierDecList implements Serializable
    serialVersionUID:
      -7228103346297172921L

- ## Package weka.classifiers.trees

  - ### Class weka.classifiers.trees.DecisionStump

    class DecisionStump extends AbstractClassifier implements Serializable
    serialVersionUID:
      1618384535950391L

    - #### Serialized Fields

      - ##### m_AttIndex

            int m_AttIndex

        The attribute used for classification.

      - ##### m_Distribution

            double[][] m_Distribution

        The distribution of class values or the means in each subset.

      - ##### m_Instances

            Instances m_Instances

        The instances used for training.

      - ##### m_SplitPoint

            double m_SplitPoint

        The split point (index respectively).

      - ##### m_ZeroR

            Classifier m_ZeroR

        a ZeroR model in case no model can be built from the data

  - ### Class weka.classifiers.trees.HoeffdingTree

    class HoeffdingTree extends AbstractClassifier implements Serializable
    serialVersionUID:
      7117521775722396251L

    - #### Serialized Fields

      - ##### m_activeLeafCount

            int m_activeLeafCount

      - ##### m_decisionNodeCount

            int m_decisionNodeCount

      - ##### m_gracePeriod

            double m_gracePeriod

        The number of instances a leaf should observe between split attempts

      - ##### m_header

            Instances m_header

      - ##### m_hoeffdingTieThreshold

            double m_hoeffdingTieThreshold

        Threshold below which a split will be forced to break ties

      - ##### m_inactiveLeafCount

            int m_inactiveLeafCount

      - ##### m_leafStrategy

            int m_leafStrategy

        The leaf prediction strategy to use

      - ##### m_minFracWeightForTwoBranchesGain

            double m_minFracWeightForTwoBranchesGain

        The minimum fraction of weight required down at least two branches for info gain splitting

      - ##### m_nbThreshold

            double m_nbThreshold

        The number of instances (total weight) a leaf should observe before allowing naive Bayes to make predictions

      - ##### m_printLeafModels

            boolean m_printLeafModels

        Print out leaf models in the case of naive Bayes or naive Bayes adaptive leaves

      - ##### m_root

            HNode m_root

      - ##### m_selectedSplitMetric

            int m_selectedSplitMetric

        The splitting metric to use

      - ##### m_splitConfidence

            double m_splitConfidence

        The allowable error in a split decision. Values closer to zero will take longer to decide

      - ##### m_splitMetric

            SplitMetric m_splitMetric

  - ### Class weka.classifiers.trees.J48

    class J48 extends AbstractClassifier implements Serializable
    serialVersionUID:
      -217733168393644444L

    - #### Serialized Fields

      - ##### m_binarySplits

            boolean m_binarySplits

        Binary splits on nominal attributes?

      - ##### m_CF

            float m_CF

        Confidence level

      - ##### m_collapseTree

            boolean m_collapseTree

        Collapse tree?

      - ##### m_doNotMakeSplitPointActualValue

            boolean m_doNotMakeSplitPointActualValue

        Do not relocate split point to actual data value

      - ##### m_minNumObj

            int m_minNumObj

        Minimum number of instances

      - ##### m_noCleanup

            boolean m_noCleanup

        Cleanup after the tree has been built.

      - ##### m_numFolds

            int m_numFolds

        Number of folds for reduced error pruning.

      - ##### m_reducedErrorPruning

            boolean m_reducedErrorPruning

        Use reduced error pruning?

      - ##### m_root

            ClassifierTree m_root

        The decision tree

      - ##### m_Seed

            int m_Seed

        Random number seed for reduced-error pruning.

      - ##### m_subtreeRaising

            boolean m_subtreeRaising

        Subtree raising to be performed?

      - ##### m_unpruned

            boolean m_unpruned

        Unpruned tree?

      - ##### m_useLaplace

            boolean m_useLaplace

        Determines whether probabilities are smoothed using Laplace correction when predictions are generated

      - ##### m_useMDLcorrection

            boolean m_useMDLcorrection

        Use MDL correction?

  - ### Class weka.classifiers.trees.LMT

    class LMT extends AbstractClassifier implements Serializable
    serialVersionUID:
      -1113212459618104943L

    - #### Serialized Fields

      - ##### m_convertNominal

            boolean m_convertNominal

        convert nominal attributes to binary ?

      - ##### m_doNotMakeSplitPointActualValue

            boolean m_doNotMakeSplitPointActualValue

        Do not relocate split point to actual data value

      - ##### m_errorOnProbabilities

            boolean m_errorOnProbabilities

        use error on probabilties instead of misclassification for stopping criterion of LogitBoost?

      - ##### m_fastRegression

            boolean m_fastRegression

        use heuristic that determines the number of LogitBoost iterations only once in the beginning?

      - ##### m_minNumInstances

            int m_minNumInstances

        minimum number of instances at which a node is considered for splitting

      - ##### m_nominalToBinary

            NominalToBinary m_nominalToBinary

        Filter to replace nominal attributes

      - ##### m_numBoostingIterations

            int m_numBoostingIterations

        if non-zero, use fixed number of iterations for LogitBoost

      - ##### m_replaceMissing

            ReplaceMissingValues m_replaceMissing

        Filter to replace missing values

      - ##### m_splitOnResiduals

            boolean m_splitOnResiduals

        split on residuals?

      - ##### m_tree

            LMTNode m_tree

        root of the logistic model tree

      - ##### m_useAIC

            boolean m_useAIC

        If true, the AIC is used to choose the best LogitBoost iteration

      - ##### m_weightTrimBeta

            double m_weightTrimBeta

        Threshold for trimming weights. Instances with a weight lower than this (as a percentage of total weights) are not included in the regression fit.

  - ### Class weka.classifiers.trees.M5P

    class M5P extends M5Base implements Serializable
    serialVersionUID:
      -6118439039768244417L

  - ### Class weka.classifiers.trees.RandomForest

    class RandomForest extends Bagging implements Serializable
    serialVersionUID:
      1116839470751428698L

    - #### Serialized Fields

      - ##### m_computeAttributeImportance

            boolean m_computeAttributeImportance

        True to compute attribute importance

  - ### Class weka.classifiers.trees.RandomTree

    class RandomTree extends AbstractClassifier implements Serializable
    serialVersionUID:
      -9051119597407396024L

    - #### Serialized Fields

      - ##### m_AllowUnclassifiedInstances

            boolean m_AllowUnclassifiedInstances

        Whether unclassified instances are allowed

      - ##### m_BreakTiesRandomly

            boolean m_BreakTiesRandomly

        Whether to break ties randomly.

      - ##### m_computeImpurityDecreases

            boolean m_computeImpurityDecreases

        Whether to store the impurity decrease/gain sum

      - ##### m_impurityDecreasees

            double[][] m_impurityDecreasees

        Indexed by attribute, each two element array contains impurity decrease/gain sum in first element and count in the second

      - ##### m_Info

            Instances m_Info

        The header information.

      - ##### m_KValue

            int m_KValue

        The number of attributes considered for a split.

      - ##### m_MaxDepth

            int m_MaxDepth

        The maximum depth of the tree (0 = unlimited)

      - ##### m_MinNum

            double m_MinNum

        Minimum number of instances for leaf.

      - ##### m_MinVarianceProp

            double m_MinVarianceProp

        The minimum proportion of the total variance (over all the data) required for split.

      - ##### m_NumFolds

            int m_NumFolds

        Determines how much data is used for backfitting

      - ##### m_randomSeed

            int m_randomSeed

        The random seed to use.

      - ##### m_Tree

            weka.classifiers.trees.RandomTree.Tree m_Tree

        The Tree object

      - ##### m_zeroR

            Classifier m_zeroR

        a ZeroR model in case no model can be built from the data

  - ### Class weka.classifiers.trees.RandomTree.Tree

    class Tree extends Object implements Serializable
    serialVersionUID:
      3549573538656522569L

    - #### Serialized Fields

      - ##### m_Attribute

            int m_Attribute

        The attribute to split on.

      - ##### m_ClassDistribution

            double[] m_ClassDistribution

        Class probabilities from the training data in the nominal case. Holds the mean in the numeric case.

      - ##### m_Distribution

            double[] m_Distribution

        Holds the sum of squared errors and the weight in the numeric case.

      - ##### m_Prop

            double[] m_Prop

        The proportions of training instances going down each branch.

      - ##### m_SplitPoint

            double m_SplitPoint

        The split point.

      - ##### m_Successors

            weka.classifiers.trees.RandomTree.Tree[] m_Successors

        The subtrees appended to this tree.

  - ### Class weka.classifiers.trees.REPTree

    class REPTree extends AbstractClassifier implements Serializable
    serialVersionUID:
      -9216785998198681299L

    - #### Serialized Fields

      - ##### m_InitialCount

            double m_InitialCount

        The initial class count

      - ##### m_MaxDepth

            int m_MaxDepth

        Upper bound on the tree depth

      - ##### m_MinNum

            double m_MinNum

        The minimum number of instances per leaf.

      - ##### m_MinVarianceProp

            double m_MinVarianceProp

        The minimum proportion of the total variance (over all the data) required for split.

      - ##### m_NoPruning

            boolean m_NoPruning

        Don't prune

      - ##### m_NumFolds

            int m_NumFolds

        Number of folds for reduced error pruning.

      - ##### m_Seed

            int m_Seed

        Seed for random data shuffling.

      - ##### m_SpreadInitialCount

            boolean m_SpreadInitialCount

        Whether to spread initial count across all values

      - ##### m_Tree

            weka.classifiers.trees.REPTree.Tree m_Tree

        The Tree object

      - ##### m_zeroR

            ZeroR m_zeroR

        ZeroR model that is used if no attributes are present.

  - ### Class weka.classifiers.trees.REPTree.Tree

    class Tree extends Object implements Serializable
    serialVersionUID:
      -1635481717888437935L

    - #### Serialized Fields

      - ##### m_Attribute

            int m_Attribute

        The attribute to split on.

      - ##### m_ClassProbs

            double[] m_ClassProbs

        Class probabilities from the training data in the nominal case. Holds the mean in the numeric case.

      - ##### m_Distribution

            double[] m_Distribution

        The (unnormalized) class distribution in the nominal case. Holds the sum of squared errors and the weight in the numeric case.

      - ##### m_HoldOutDist

            double[] m_HoldOutDist

        Class distribution of hold-out set at node in the nominal case. Straight sum of weights plus sum of weighted targets in the numeric case (i.e. array has only two elements).

      - ##### m_HoldOutError

            double m_HoldOutError

        The hold-out error of the node. The number of miss-classified instances in the nominal case, the sum of squared errors in the numeric case.

      - ##### m_Info

            Instances m_Info

        The header information (for printing the tree).

      - ##### m_Prop

            double[] m_Prop

        The proportions of training instances going down each branch.

      - ##### m_SplitPoint

            double m_SplitPoint

        The split point.

      - ##### m_Successors

            weka.classifiers.trees.REPTree.Tree[] m_Successors

        The subtrees of this tree.

- ## Package weka.classifiers.trees.ht

  - ### Class weka.classifiers.trees.ht.ActiveHNode

    class ActiveHNode extends LeafNode implements Serializable
    serialVersionUID:
      3284585939739561683L

    - #### Serialized Fields

      - ##### m_nodeStats

            Map<String,ConditionalSufficientStats> m_nodeStats

        Statistics for nominal or numeric attributes conditioned on the class

      - ##### m_weightSeenAtLastSplitEval

            double m_weightSeenAtLastSplitEval

        The weight of instances seen at the last split evaluation

  - ### Class weka.classifiers.trees.ht.ConditionalSufficientStats

    class ConditionalSufficientStats extends Object implements Serializable
    serialVersionUID:
      8724787722646808376L

    - #### Serialized Fields

      - ##### m_classLookup

            Map<String,Object> m_classLookup

        Lookup by class value

  - ### Class weka.classifiers.trees.ht.GaussianConditionalSufficientStats

    class GaussianConditionalSufficientStats extends ConditionalSufficientStats implements Serializable
    serialVersionUID:
      -1527915607201784762L

    - #### Serialized Fields

      - ##### m_maxValObservedPerClass

            Map<String,Double> m_maxValObservedPerClass

      - ##### m_minValObservedPerClass

            Map<String,Double> m_minValObservedPerClass

      - ##### m_numBins

            int m_numBins

  - ### Class weka.classifiers.trees.ht.GaussianConditionalSufficientStats.GaussianEstimator

    class GaussianEstimator extends UnivariateNormalEstimator implements Serializable
    serialVersionUID:
      4756032800685001315L

  - ### Class weka.classifiers.trees.ht.GiniSplitMetric

    class GiniSplitMetric extends SplitMetric implements Serializable
    serialVersionUID:
      -2037586582742660298L

  - ### Class weka.classifiers.trees.ht.HNode

    class HNode extends Object implements Serializable
    serialVersionUID:
      197233928177240264L

    - #### Serialized Fields

      - ##### m_classDistribution

            Map<String,WeightMass> m_classDistribution

        Class distribution at this node

      - ##### m_leafNum

            int m_leafNum

        Holds the leaf number (if this is a leaf)

      - ##### m_nodeNum

            int m_nodeNum

        Holds the node number (for graphing purposes)

  - ### Class weka.classifiers.trees.ht.InactiveHNode

    class InactiveHNode extends LeafNode implements Serializable
    serialVersionUID:
      -8747567733141700911L

  - ### Class weka.classifiers.trees.ht.InfoGainSplitMetric

    class InfoGainSplitMetric extends SplitMetric implements Serializable
    serialVersionUID:
      2173840581308675428L

    - #### Serialized Fields

      - ##### m_minFracWeightForTwoBranches

            double m_minFracWeightForTwoBranches

  - ### Class weka.classifiers.trees.ht.LeafNode

    class LeafNode extends HNode implements Serializable
    serialVersionUID:
      -3359429731894384404L

    - #### Serialized Fields

      - ##### m_parentBranch

            String m_parentBranch

        Parent branch leading to this node

      - ##### m_parentNode

            SplitNode m_parentNode

        Parent split node

      - ##### m_theNode

            HNode m_theNode

        The actual node for this leaf

  - ### Class weka.classifiers.trees.ht.NBNode

    class NBNode extends ActiveHNode implements Serializable
    serialVersionUID:
      -1872415764817690961L

    - #### Serialized Fields

      - ##### m_bayes

            NaiveBayesUpdateable m_bayes

        The naive Bayes model at the node

      - ##### m_nbWeightThreshold

            double m_nbWeightThreshold

        The weight of instances that need to be seen by this node before allowing naive Bayes to make predictions

  - ### Class weka.classifiers.trees.ht.NBNodeAdaptive

    class NBNodeAdaptive extends NBNode implements Serializable
    serialVersionUID:
      -4509802312019989686L

    - #### Serialized Fields

      - ##### m_majClassCorrectWeight

            double m_majClassCorrectWeight

        The number of correct predictions made by the majority class

      - ##### m_nbCorrectWeight

            double m_nbCorrectWeight

        The number of correct predictions made by naive Bayes

  - ### Class weka.classifiers.trees.ht.NominalConditionalSufficientStats

    class NominalConditionalSufficientStats extends ConditionalSufficientStats implements Serializable
    serialVersionUID:
      -669902060601313488L

    - #### Serialized Fields

      - ##### m_missingWeight

            double m_missingWeight

      - ##### m_totalWeight

            double m_totalWeight

  - ### Class weka.classifiers.trees.ht.NominalConditionalSufficientStats.ValueDistribution

    class ValueDistribution extends Object implements Serializable
    serialVersionUID:
      -61711544350888154L

    - #### Serialized Fields

      - ##### m_dist

            Map<Integer,WeightMass> m_dist

      - ##### m_sum

            double m_sum

  - ### Class weka.classifiers.trees.ht.Split

    class Split extends Object implements Serializable
    serialVersionUID:
      5390368487675958092L

    - #### Serialized Fields

      - ##### m_splitAttNames

            List<String> m_splitAttNames

        name(s) of attribute(s) involved in the split

  - ### Class weka.classifiers.trees.ht.SplitMetric

    class SplitMetric extends Object implements Serializable
    serialVersionUID:
      2891555018707080818L

  - ### Class weka.classifiers.trees.ht.SplitNode

    class SplitNode extends HNode implements Serializable
    serialVersionUID:
      1558033628618451073L

    - #### Serialized Fields

      - ##### m_children

            Map<String,HNode> m_children

        Child nodes

      - ##### m_split

            Split m_split

        The split itself

  - ### Class weka.classifiers.trees.ht.UnivariateNominalMultiwaySplit

    class UnivariateNominalMultiwaySplit extends Split implements Serializable
    serialVersionUID:
      -9094590488097956665L

  - ### Class weka.classifiers.trees.ht.UnivariateNumericBinarySplit

    class UnivariateNumericBinarySplit extends Split implements Serializable
    serialVersionUID:
      -7392204582942741097L

    - #### Serialized Fields

      - ##### m_splitPoint

            double m_splitPoint

        The split point

  - ### Class weka.classifiers.trees.ht.WeightMass

    class WeightMass extends Object implements Serializable
    serialVersionUID:
      6794839107050779425L

    - #### Serialized Fields

      - ##### m_weight

            double m_weight

- ## Package weka.classifiers.trees.j48

  - ### Class weka.classifiers.trees.j48.BinC45ModelSelection

    class BinC45ModelSelection extends ModelSelection implements Serializable
    serialVersionUID:
      179170923545122001L

    - #### Serialized Fields

      - ##### m_allData

            Instances m_allData

        The FULL training dataset.

      - ##### m_doNotMakeSplitPointActualValue

            boolean m_doNotMakeSplitPointActualValue

        Do not relocate split point to actual data value

      - ##### m_minNoObj

            int m_minNoObj

        Minimum number of instances in interval.

      - ##### m_useMDLcorrection

            boolean m_useMDLcorrection

        Use MDL correction?

  - ### Class weka.classifiers.trees.j48.BinC45Split

    class BinC45Split extends ClassifierSplitModel implements Serializable
    serialVersionUID:
      -1278776919563022474L

    - #### Serialized Fields

      - ##### m_attIndex

            int m_attIndex

        Attribute to split on.

      - ##### m_gainRatio

            double m_gainRatio

        GainRatio of split.

      - ##### m_infoGain

            double m_infoGain

        InfoGain of split.

      - ##### m_minNoObj

            int m_minNoObj

        Minimum number of objects in a split.

      - ##### m_splitPoint

            double m_splitPoint

        Value of split point.

      - ##### m_sumOfWeights

            double m_sumOfWeights

        The sum of the weights of the instances.

      - ##### m_useMDLcorrection

            boolean m_useMDLcorrection

        Use MDL correction?

  - ### Class weka.classifiers.trees.j48.C45ModelSelection

    class C45ModelSelection extends ModelSelection implements Serializable
    serialVersionUID:
      3372204862440821989L

    - #### Serialized Fields

      - ##### m_allData

            Instances m_allData

        All the training data

      - ##### m_doNotMakeSplitPointActualValue

            boolean m_doNotMakeSplitPointActualValue

        Do not relocate split point to actual data value

      - ##### m_minNoObj

            int m_minNoObj

        Minimum number of objects in interval.

      - ##### m_useMDLcorrection

            boolean m_useMDLcorrection

        Use MDL correction?

  - ### Class weka.classifiers.trees.j48.C45PruneableClassifierTree

    class C45PruneableClassifierTree extends ClassifierTree implements Serializable
    serialVersionUID:
      -4813820170260388194L

    - #### Serialized Fields

      - ##### m_CF

            float m_CF

        The confidence factor for pruning.

      - ##### m_cleanup

            boolean m_cleanup

        Cleanup after the tree has been built.

      - ##### m_collapseTheTree

            boolean m_collapseTheTree

        True if the tree is to be collapsed.

      - ##### m_pruneTheTree

            boolean m_pruneTheTree

        True if the tree is to be pruned.

      - ##### m_subtreeRaising

            boolean m_subtreeRaising

        Is subtree raising to be performed?

  - ### Class weka.classifiers.trees.j48.C45Split

    class C45Split extends ClassifierSplitModel implements Serializable
    serialVersionUID:
      3064079330067903161L

    - #### Serialized Fields

      - ##### m_attIndex

            int m_attIndex

        Attribute to split on.

      - ##### m_complexityIndex

            int m_complexityIndex

        Desired number of branches.

      - ##### m_gainRatio

            double m_gainRatio

        GainRatio of split.

      - ##### m_index

            int m_index

        Number of split points.

      - ##### m_infoGain

            double m_infoGain

        InfoGain of split.

      - ##### m_minNoObj

            int m_minNoObj

        Minimum number of objects in a split.

      - ##### m_splitPoint

            double m_splitPoint

        Value of split point.

      - ##### m_sumOfWeights

            double m_sumOfWeights

        The sum of the weights of the instances.

      - ##### m_useMDLcorrection

            boolean m_useMDLcorrection

        Use MDL correction?

  - ### Class weka.classifiers.trees.j48.ClassifierSplitModel

    class ClassifierSplitModel extends Object implements Serializable
    serialVersionUID:
      4280730118393457457L

    - #### Serialized Fields

      - ##### m_distribution

            Distribution m_distribution

        Distribution of class values.

      - ##### m_numSubsets

            int m_numSubsets

        Number of created subsets.

  - ### Class weka.classifiers.trees.j48.ClassifierTree

    class ClassifierTree extends Object implements Serializable
    serialVersionUID:
      -8722249377542734193L

    - #### Serialized Fields

      - ##### m_id

            int m_id

        The id for the node.

      - ##### m_isEmpty

            boolean m_isEmpty

        True if node is empty.

      - ##### m_isLeaf

            boolean m_isLeaf

        True if node is leaf.

      - ##### m_localModel

            ClassifierSplitModel m_localModel

        Local model at node.

      - ##### m_sons

            ClassifierTree[] m_sons

        References to sons.

      - ##### m_test

            Distribution m_test

        The pruning instances.

      - ##### m_toSelectModel

            ModelSelection m_toSelectModel

        The model selection method.

      - ##### m_train

            Instances m_train

        The training instances.

  - ### Class weka.classifiers.trees.j48.Distribution

    class Distribution extends Object implements Serializable
    serialVersionUID:
      8526859638230806576L

    - #### Serialized Fields

      - ##### m_perBag

            double[] m_perBag

        Weight of instances per bag.

      - ##### m_perClass

            double[] m_perClass

        Weight of instances per class.

      - ##### m_perClassPerBag

            double[][] m_perClassPerBag

        Weight of instances per class per bag.

      - ##### totaL

            double totaL

        Total weight of instances.

  - ### Class weka.classifiers.trees.j48.EntropyBasedSplitCrit

    class EntropyBasedSplitCrit extends SplitCriterion implements Serializable
    serialVersionUID:
      -2618691439791653056L

  - ### Class weka.classifiers.trees.j48.EntropySplitCrit

    class EntropySplitCrit extends EntropyBasedSplitCrit implements Serializable
    serialVersionUID:
      5986252682266803935L

  - ### Class weka.classifiers.trees.j48.GainRatioSplitCrit

    class GainRatioSplitCrit extends EntropyBasedSplitCrit implements Serializable
    serialVersionUID:
      -433336694718670930L

  - ### Class weka.classifiers.trees.j48.InfoGainSplitCrit

    class InfoGainSplitCrit extends EntropyBasedSplitCrit implements Serializable
    serialVersionUID:
      4892105020180728499L

  - ### Class weka.classifiers.trees.j48.ModelSelection

    class ModelSelection extends Object implements Serializable
    serialVersionUID:
      -4850147125096133642L

  - ### Class weka.classifiers.trees.j48.NBTreeClassifierTree

    class NBTreeClassifierTree extends ClassifierTree implements Serializable
    serialVersionUID:
      -4472639447877404786L

  - ### Class weka.classifiers.trees.j48.NBTreeModelSelection

    class NBTreeModelSelection extends ModelSelection implements Serializable
    serialVersionUID:
      990097748931976704L

    - #### Serialized Fields

      - ##### m_allData

            Instances m_allData

        All the training data

      - ##### m_minNoObj

            int m_minNoObj

        Minimum number of objects in interval.

  - ### Class weka.classifiers.trees.j48.NBTreeNoSplit

    class NBTreeNoSplit extends ClassifierSplitModel implements Serializable
    serialVersionUID:
      7824804381545259618L

    - #### Serialized Fields

      - ##### m_disc

            Discretize m_disc

        the discretizer used

      - ##### m_errors

            double m_errors

        errors on the training data at this node

      - ##### m_nb

            NaiveBayesUpdateable m_nb

        the naive bayes classifier

  - ### Class weka.classifiers.trees.j48.NBTreeSplit

    class NBTreeSplit extends ClassifierSplitModel implements Serializable
    serialVersionUID:
      8922627123884975070L

    - #### Serialized Fields

      - ##### m_attIndex

            int m_attIndex

        Attribute to split on.

      - ##### m_c45S

            C45Split m_c45S

      - ##### m_complexityIndex

            int m_complexityIndex

        Desired number of branches.

      - ##### m_errors

            double m_errors

        The weight of the instances incorrectly classified by the naive bayes models arising from this split

      - ##### m_globalNB

            NBTreeNoSplit m_globalNB

        The global naive bayes model for this node

      - ##### m_sumOfWeights

            double m_sumOfWeights

        The sum of the weights of the instances.

  - ### Class weka.classifiers.trees.j48.NoSplit

    class NoSplit extends ClassifierSplitModel implements Serializable
    serialVersionUID:
      -1292620749331337546L

  - ### Class weka.classifiers.trees.j48.PruneableClassifierTree

    class PruneableClassifierTree extends ClassifierTree implements Serializable
    serialVersionUID:
      -555775736857600201L

    - #### Serialized Fields

      - ##### m_cleanup

            boolean m_cleanup

        Cleanup after the tree has been built.

      - ##### m_seed

            int m_seed

        The random number seed.

      - ##### numSets

            int numSets

        How many subsets of equal size? One used for pruning, the rest for training.

      - ##### pruneTheTree

            boolean pruneTheTree

        True if the tree is to be pruned.

  - ### Class weka.classifiers.trees.j48.SplitCriterion

    class SplitCriterion extends Object implements Serializable
    serialVersionUID:
      5490996638027101259L

- ## Package weka.classifiers.trees.lmt

  - ### Class weka.classifiers.trees.lmt.LMTNode

    class LMTNode extends LogisticBase implements Serializable
    serialVersionUID:
      1862737145870398755L

    - #### Serialized Fields

      - ##### m_alpha

            double m_alpha

        Alpha-value (for pruning) at the node

      - ##### m_fastRegression

            boolean m_fastRegression

        Use heuristic that determines the number of LogitBoost iterations only once in the beginning?

      - ##### m_id

            int m_id

        Node id

      - ##### m_isLeaf

            boolean m_isLeaf

        True if node is leaf

      - ##### m_leafModelNum

            int m_leafModelNum

        ID of logistic model at leaf

      - ##### m_localModel

            ClassifierSplitModel m_localModel

        The ClassifierSplitModel (for splitting)

      - ##### m_minNumInstances

            int m_minNumInstances

        minimum number of instances at which a node is considered for splitting

      - ##### m_modelSelection

            ModelSelection m_modelSelection

        ModelSelection object (for splitting)

      - ##### m_nominalToBinary

            NominalToBinary m_nominalToBinary

        Filter to convert nominal attributes to binary

      - ##### m_numIncorrectModel

            double m_numIncorrectModel

        Weighted number of training examples currently misclassified by the logistic model at the node

      - ##### m_numIncorrectTree

            double m_numIncorrectTree

        Weighted number of training examples currently misclassified by the subtree rooted at the node

      - ##### m_numInstances

            int m_numInstances

        Number of instances at the node

      - ##### m_sons

            LMTNode[] m_sons

        Array of children of the node

      - ##### m_totalInstanceWeight

            double m_totalInstanceWeight

        Total number of training instances.

  - ### Class weka.classifiers.trees.lmt.LogisticBase

    class LogisticBase extends AbstractClassifier implements Serializable
    serialVersionUID:
      168765678097825064L

    - #### Serialized Fields

      - ##### m_errorOnProbabilities

            boolean m_errorOnProbabilities

        Use error on probabilities for stopping criterion of LogitBoost?

      - ##### m_fixedNumIterations

            int m_fixedNumIterations

        Use fixed number of iterations for LogitBoost? (if negative, cross-validate number of iterations)

      - ##### m_heuristicStop

            int m_heuristicStop

        Use heuristic to stop performing LogitBoost iterations earlier? If enabled, LogitBoost is stopped if the current (local) minimum of the error on a test set as a function of the number of iterations has not changed for m_heuristicStop iterations.

      - ##### m_maxIterations

            int m_maxIterations

        The maximum number of LogitBoost iterations

      - ##### m_numClasses

            int m_numClasses

        The number of different classes

      - ##### m_numericData

            Instances m_numericData

        Numeric version of the training data. Original class is replaced by a numeric pseudo-class.

      - ##### m_numericDataHeader

            Instances m_numericDataHeader

        Header-only version of the numeric version of the training data

      - ##### m_numParameters

            double m_numParameters

        Effective number of parameters used for AIC / BIC automatic stopping

      - ##### m_numRegressions

            int m_numRegressions

        The number of LogitBoost iterations performed.

      - ##### m_regressions

            SimpleLinearRegression[][] m_regressions

        Array holding the simple regression functions fit by LogitBoost

      - ##### m_train

            Instances m_train

        Training data

      - ##### m_useAIC

            boolean m_useAIC

        If true, the AIC is used to choose the best iteration

      - ##### m_useCrossValidation

            boolean m_useCrossValidation

        Use cross-validation to determine best number of LogitBoost iterations ?

      - ##### m_weightTrimBeta

            double m_weightTrimBeta

        Threshold for trimming weights. Instances with a weight lower than this (as a percentage of total weights) are not included in the regression fit.

  - ### Class weka.classifiers.trees.lmt.ResidualModelSelection

    class ResidualModelSelection extends ModelSelection implements Serializable
    serialVersionUID:
      -293098783159385148L

    - #### Serialized Fields

      - ##### m_minInfoGain

            double m_minInfoGain

        Minimum information gain for split

      - ##### m_minNumInstances

            int m_minNumInstances

        Minimum number of instances for leaves

  - ### Class weka.classifiers.trees.lmt.ResidualSplit

    class ResidualSplit extends ClassifierSplitModel implements Serializable
    serialVersionUID:
      -5055883734183713525L

    - #### Serialized Fields

      - ##### m_attIndex

            int m_attIndex

        The index of the attribute selected for the split

      - ##### m_attribute

            Attribute m_attribute

        The attribute selected for the split

      - ##### m_data

            Instances m_data

        The set of instances

      - ##### m_dataWs

            double[][] m_dataWs

        The LogitBoost-weights for the set of instances

      - ##### m_dataZs

            double[][] m_dataZs

        The Z-values (LogitBoost response) for the set of instances

      - ##### m_numClasses

            int m_numClasses

        Number of classed

      - ##### m_numInstances

            int m_numInstances

        Number of instances in the set

      - ##### m_splitPoint

            double m_splitPoint

        The split point (for numeric attributes)

  - ### Class weka.classifiers.trees.lmt.SimpleLinearRegression

    class SimpleLinearRegression extends Object implements Serializable
    serialVersionUID:
      1779336022895414137L

    - #### Serialized Fields

      - ##### m_attributeIndex

            int m_attributeIndex

        The index of the chosen attribute

      - ##### m_intercept

            double m_intercept

        The intercept

      - ##### m_slope

            double m_slope

        The slope

- ## Package weka.classifiers.trees.m5

  - ### Class weka.classifiers.trees.m5.CorrelationSplitInfo

    class CorrelationSplitInfo extends Object implements Serializable
    serialVersionUID:
      4212734895125452770L

    - #### Serialized Fields

      - ##### m_maxImpurity

            double m_maxImpurity

        the maximum impurity reduction

      - ##### m_number

            int m_number

        the number of instances

      - ##### m_position

            int m_position

      - ##### m_splitAttr

            int m_splitAttr

        the attribute being tested

      - ##### m_splitValue

            double m_splitValue

        the best value on which to split

  - ### Class weka.classifiers.trees.m5.M5Base

    class M5Base extends AbstractClassifier implements Serializable
    serialVersionUID:
      -4022221950191647679L

    - #### Serialized Fields

      - ##### m_generateRules

            boolean m_generateRules

        generate a decision list instead of a single tree.

      - ##### m_instances

            Instances m_instances

        the instances covered by the tree/rules

      - ##### m_minNumInstances

            double m_minNumInstances

        The minimum number of instances to allow at a leaf node

      - ##### m_nominalToBinary

            NominalToBinary m_nominalToBinary

        filter to convert nominal attributes to binary

      - ##### m_regressionTree

            boolean m_regressionTree

        Make a regression tree/rule instead of a model tree/rule

      - ##### m_removeUseless

            RemoveUseless m_removeUseless

        for removing useless attributes

      - ##### m_replaceMissing

            ReplaceMissingValues m_replaceMissing

        filter to fill in missing values

      - ##### m_ruleSet

            ArrayList<Rule> m_ruleSet

        the rule set

      - ##### m_saveInstances

            boolean m_saveInstances

        Save instances at each node in an M5 tree for visualization purposes.

      - ##### m_unsmoothedPredictions

            boolean m_unsmoothedPredictions

        use unsmoothed predictions

      - ##### m_useUnpruned

            boolean m_useUnpruned

        Do not prune tree/rules

  - ### Class weka.classifiers.trees.m5.PreConstructedLinearModel

    class PreConstructedLinearModel extends AbstractClassifier implements Serializable
    serialVersionUID:
      2030974097051713247L

    - #### Serialized Fields

      - ##### m_coefficients

            double[] m_coefficients

        The coefficients

      - ##### m_instancesHeader

            Instances m_instancesHeader

        Holds the instances header for printing the model

      - ##### m_intercept

            double m_intercept

        The intercept

      - ##### m_numParameters

            int m_numParameters

        number of coefficients in the model

  - ### Class weka.classifiers.trees.m5.Rule

    class Rule extends Object implements Serializable
    serialVersionUID:
      -4458627451682483204L

    - #### Serialized Fields

      - ##### m_classIndex

            int m_classIndex

        the class index

      - ##### m_covered

            Instances m_covered

        the instances covered by this rule

      - ##### m_globalAbsDev

            double m_globalAbsDev

        the absolute deviation of the class for all the instances

      - ##### m_globalStdDev

            double m_globalStdDev

        the standard deviation of the class for all the instances

      - ##### m_instances

            Instances m_instances

        the instances covered by this rule

      - ##### m_internalNodes

            RuleNode[] m_internalNodes

        the corresponding internal nodes. Used for smoothing rules.

      - ##### m_minNumInstances

            double m_minNumInstances

        The minimum number of instances to allow at a leaf node

      - ##### m_notCovered

            Instances m_notCovered

        the instances not covered by this rule

      - ##### m_numCovered

            int m_numCovered

        the number of instances covered by this rule

      - ##### m_numDecimalPlaces

            int m_numDecimalPlaces

        The number of decimal places used for printing this rule.

      - ##### m_numInstances

            int m_numInstances

        the number of instances in the dataset

      - ##### m_regressionTree

            boolean m_regressionTree

        Make a regression tree instead of a model tree

      - ##### m_relOps

            int[] m_relOps

        the corresponding relational operators (0 = "<=", 1 = ">")

      - ##### m_ruleModel

            RuleNode m_ruleModel

        the leaf encapsulating the linear model for this rule

      - ##### m_saveInstances

            boolean m_saveInstances

        Save instances at each node in an M5 tree for visualization purposes.

      - ##### m_smoothPredictions

            boolean m_smoothPredictions

        use the original m5 smoothing procedure

      - ##### m_splitAtts

            int[] m_splitAtts

        the indexes of the attributes used to split on for this rule

      - ##### m_splitVals

            double[] m_splitVals

        the corresponding values of the split points

      - ##### m_topOfTree

            RuleNode m_topOfTree

        the top of the m5 tree for this rule

      - ##### m_useTree

            boolean m_useTree

        use a pruned m5 tree rather than make a rule

      - ##### m_useUnpruned

            boolean m_useUnpruned

        Build unpruned tree/rule

  - ### Class weka.classifiers.trees.m5.RuleNode

    class RuleNode extends AbstractClassifier implements Serializable
    serialVersionUID:
      1979807611124337144L

    - #### Serialized Fields

      - ##### m_classIndex

            int m_classIndex

        the class index

      - ##### m_devFraction

            double m_devFraction

        a node will not be split if its class standard deviation is less than 5% of the class standard deviation of all the instances

      - ##### m_globalAbsDeviation

            double m_globalAbsDeviation

        the absolute deviation of the global class

      - ##### m_globalDeviation

            double m_globalDeviation

        a node will not be split if the class deviation of its instances is less than m_devFraction of the deviation of the global class

      - ##### m_id

            int m_id

        Node id.

      - ##### m_indices

            int[] m_indices

        Indices of the attributes to be used in generating a linear model at this node

      - ##### m_instances

            Instances m_instances

        instances reaching this node

      - ##### m_isLeaf

            boolean m_isLeaf

        Node is a leaf

      - ##### m_leafModelNum

            int m_leafModelNum

        the number assigned to the linear model if this node is a leaf. = 0 if this node is not a leaf

      - ##### m_left

            RuleNode m_left

        left child node

      - ##### m_nodeModel

            PreConstructedLinearModel m_nodeModel

        the linear model at this node

      - ##### m_numAttributes

            int m_numAttributes

        the number of attributes

      - ##### m_numInstances

            int m_numInstances

        the number of instances reaching this node

      - ##### m_numParameters

            int m_numParameters

        the number of paramters in the chosen model for this node---either the subtree model or the linear model. The constant term is counted as a paramter---this is for pruning purposes

      - ##### m_parent

            RuleNode m_parent

        the parent of this node

      - ##### m_pruningMultiplier

            double m_pruningMultiplier

      - ##### m_regressionTree

            boolean m_regressionTree

        Make a regression tree instead of a model tree

      - ##### m_right

            RuleNode m_right

        right child node

      - ##### m_rootMeanSquaredError

            double m_rootMeanSquaredError

        the mean squared error of the model at this node (either linear or subtree)

      - ##### m_saveInstances

            boolean m_saveInstances

        Save the instances at each node (for visualizing in the Explorer's treevisualizer.

      - ##### m_splitAtt

            int m_splitAtt

        attribute this node splits on

      - ##### m_splitNum

            double m_splitNum

        a node will not be split if it contains less then m_splitNum instances

      - ##### m_splitValue

            double m_splitValue

        the value of the split attribute

  - ### Class weka.classifiers.trees.m5.YongSplitInfo

    class YongSplitInfo extends Object implements Serializable
    serialVersionUID:
      1864267581079767881L

    - #### Serialized Fields

      - ##### first

            int first

      - ##### last

            int last

      - ##### leftAve

            double leftAve

      - ##### maxImpurity

            double maxImpurity

      - ##### number

            int number

      - ##### position

            int position

      - ##### rightAve

            double rightAve

      - ##### splitAttr

            int splitAttr

      - ##### splitValue

            double splitValue

- ## Package weka.clusterers

  - ### Class weka.clusterers.AbstractClusterer

    class AbstractClusterer extends Object implements Serializable
    serialVersionUID:
      -6099962589663877632L

    - #### Serialized Fields

      - ##### m_Debug

            boolean m_Debug

        Whether the clusterer is run in debug mode.

      - ##### m_DoNotCheckCapabilities

            boolean m_DoNotCheckCapabilities

        Whether capabilities should not be checked before clusterer is built.

  - ### Class weka.clusterers.AbstractDensityBasedClusterer

    class AbstractDensityBasedClusterer extends AbstractClusterer implements Serializable
    serialVersionUID:
      -5950728041704213845L

  - ### Class weka.clusterers.Canopy

    class Canopy extends RandomizableClusterer implements Serializable
    serialVersionUID:
      2067574593448223334L

    - #### Serialized Fields

      - ##### m_canopies

            Instances m_canopies

        The canopy centers

      - ##### m_canopyCenters

            List<double[][]> m_canopyCenters

      - ##### m_canopyNumMissingForNumerics

            List<double[]> m_canopyNumMissingForNumerics

      - ##### m_canopyT2Density

            List<double[]> m_canopyT2Density

        The T2 density of each canopy

      - ##### m_clusterCanopies

            List<long[]> m_clusterCanopies

        The list of canopies that each canopy is a member of (according to the T1 radius, which can overlap). Each bit position in the long values corresponds to one canopy. Outer list order corresponds to the order of the instances that store the actual canopy centers

      - ##### m_didPruneLastTime

            boolean m_didPruneLastTime

        True if the pruning operation did remove at least one low density canopy the last time it was invoked

      - ##### m_distanceFunction

            NormalizableDistance m_distanceFunction

        The distance function to use

      - ##### m_dontReplaceMissing

            boolean m_dontReplaceMissing

        Replace missing values globally when running in batch mode?

      - ##### m_instanceCount

            int m_instanceCount

        Number of training instances seen so far

      - ##### m_maxCanopyCandidates

            int m_maxCanopyCandidates

        The maximum number of candidate canopies to hold in memory at any one time

      - ##### m_minClusterDensity

            double m_minClusterDensity

        The minimum cluster density (according to T2 distance) allowed. Used when periodically pruning candidate canopies

      - ##### m_missingValuesReplacer

            Filter m_missingValuesReplacer

        If not null, then this is expected to be a filter that can replace missing values immediately (at training and testing time)

      - ##### m_numClustersRequested

            int m_numClustersRequested

        Default is to let the t2 radius determine how many canopies/clusters are formed

      - ##### m_periodicPruningRate

            int m_periodicPruningRate

        Prune low-density candidate canopies after every x instances have been seen

      - ##### m_t1

            double m_t1

        Outer radius

      - ##### m_t2

            double m_t2

        Inner radius

      - ##### m_trainingData

            Instances m_trainingData

        Used to pad out number of cluster centers if fewer canopies are generated than the number of requested clusters and we are running in batch mode.

      - ##### m_userT1

            double m_userT1

        < 0 indicates the multiplier to use for T2 when setting T1, otherwise the value is take as is

      - ##### m_userT2

            double m_userT2

        < 0 means use the heuristic based on std. dev. to set the t2 radius

  - ### Class weka.clusterers.ClusterEvaluation

    class ClusterEvaluation extends Object implements Serializable
    serialVersionUID:
      -830188327319128005L

    - #### Serialized Fields

      - ##### m_classToCluster

            int[] m_classToCluster

        will hold the mapping of classes to clusters (for class based evaluation)

      - ##### m_clusterAssignments

            double[] m_clusterAssignments

        holds the assigments of instances to clusters for a particular testing dataset

      - ##### m_Clusterer

            Clusterer m_Clusterer

        the clusterer

      - ##### m_clusteringResults

            StringBuffer m_clusteringResults

        holds a string describing the results of clustering the training data

      - ##### m_logL

            double m_logL

        holds the average log likelihood for a particular testing dataset if the clusterer is a DensityBasedClusterer

      - ##### m_numClusters

            int m_numClusters

        holds the number of clusters found by the clusterer

  - ### Class weka.clusterers.Cobweb

    class Cobweb extends RandomizableClusterer implements Serializable
    serialVersionUID:
      928406656495092318L

    - #### Serialized Fields

      - ##### m_acuity

            double m_acuity

        Acuity (minimum standard deviation).

      - ##### m_cobwebTree

            Cobweb.CNode m_cobwebTree

        Holds the root of the Cobweb tree.

      - ##### m_cutoff

            double m_cutoff

        Cutoff (minimum category utility).

      - ##### m_numberMerges

            int m_numberMerges

        the number of merges that happened

      - ##### m_numberOfClusters

            int m_numberOfClusters

        Number of clusters (nodes in the tree). Must never be queried directly, only via the method numberOfClusters(). Otherwise it's not guaranteed that it contains the correct value.
        See Also:
          - `Cobweb.numberOfClusters()`
          - `Cobweb.m_numberOfClustersDetermined`

      - ##### m_numberOfClustersDetermined

            boolean m_numberOfClustersDetermined

        whether the number of clusters was already determined

      - ##### m_numberSplits

            int m_numberSplits

        the number of splits that happened

      - ##### m_saveInstances

            boolean m_saveInstances

        Output instances in graph representation of Cobweb tree (Allows instances at nodes in the tree to be visualized in the Explorer).

  - ### Class weka.clusterers.Cobweb.CNode

    class CNode extends Object implements Serializable
    serialVersionUID:
      3452097436933325631L

    - #### Serialized Fields

      - ##### m_attStats

            AttributeStats[] m_attStats

        Within cluster attribute statistics

      - ##### m_children

            ArrayList<Cobweb.CNode> m_children

        Children of this node

      - ##### m_clusterInstances

            Instances m_clusterInstances

        Instances at this node

      - ##### m_clusterNum

            int m_clusterNum

        Cluster number of this node

      - ##### m_numAttributes

            int m_numAttributes

        Number of attributes

      - ##### m_totalInstances

            double m_totalInstances

        Total instances at this node

  - ### Class weka.clusterers.EM

    class EM extends RandomizableDensityBasedClusterer implements Serializable
    serialVersionUID:
      8348181483812829475L

    - #### Serialized Fields

      - ##### m_cvFolds

            int m_cvFolds

        The number of folds to use for cross-validation

      - ##### m_displayModelInOldFormat

            boolean m_displayModelInOldFormat

        display model output in old-style format

      - ##### m_executionSlots

            int m_executionSlots

        Number of threads to use for E and M steps

      - ##### m_initialNumClusters

            int m_initialNumClusters

        the initial number of clusters requested by the user--- -1 if xval is to be used to find the number of clusters

      - ##### m_iterationsPerformed

            int m_iterationsPerformed

        The actual number of iterations performed

      - ##### m_max_iterations

            int m_max_iterations

        maximum iterations to perform

      - ##### m_maxValues

            double[] m_maxValues

        attribute max values

      - ##### m_minLogLikelihoodImprovementCV

            double m_minLogLikelihoodImprovementCV

        Minimum improvement to increase number of clusters when cross-validating

      - ##### m_minLogLikelihoodImprovementIterating

            double m_minLogLikelihoodImprovementIterating

        Minimum improvement in log likelihood when iterating

      - ##### m_minStdDev

            double m_minStdDev

        default minimum standard deviation

      - ##### m_minStdDevPerAtt

            double[] m_minStdDevPerAtt

      - ##### m_minValues

            double[] m_minValues

        attribute min values

      - ##### m_model

            Estimator[][] m_model

        hold the discrete estimators for each cluster

      - ##### m_modelNormal

            double[][][] m_modelNormal

        hold the normal estimators for each cluster

      - ##### m_modelNormalPrev

            double[][][] m_modelNormalPrev

      - ##### m_modelPrev

            Estimator[][] m_modelPrev

      - ##### m_num_attribs

            int m_num_attribs

        number of attributes

      - ##### m_num_clusters

            int m_num_clusters

        number of clusters selected by the user or cross validation

      - ##### m_num_instances

            int m_num_instances

        number of training instances

      - ##### m_NumKMeansRuns

            int m_NumKMeansRuns

        The number of runs of k-means to perform

      - ##### m_priors

            double[] m_priors

        the prior probabilities for clusters

      - ##### m_priorsPrev

            double[] m_priorsPrev

      - ##### m_replaceMissing

            ReplaceMissingValues m_replaceMissing

        globally replace missing values

      - ##### m_rr

            Random m_rr

        random number generator

      - ##### m_theInstances

            Instances m_theInstances

        full training instances

      - ##### m_training

            boolean m_training

        False once training has completed

      - ##### m_upperBoundNumClustersCV

            int m_upperBoundNumClustersCV

        Don't consider more clusters than this under CV (-1 means no upper bound)

      - ##### m_verbose

            boolean m_verbose

        Verbose?

      - ##### m_weights

            double[][] m_weights

        hold the weights of each instance for each cluster

  - ### Class weka.clusterers.FarthestFirst

    class FarthestFirst extends RandomizableClusterer implements Serializable
    serialVersionUID:
      7499838100631329509L

    - #### Serialized Fields

      - ##### m_ClusterCentroids

            Instances m_ClusterCentroids

        holds the cluster centroids

      - ##### m_instances

            Instances m_instances

        training instances, not necessary to keep, could be replaced by m_ClusterCentroids where needed for header info

      - ##### m_Max

            double[] m_Max

        attribute max values

      - ##### m_Min

            double[] m_Min

        attribute min values

      - ##### m_NumClusters

            int m_NumClusters

        number of clusters to generate

      - ##### m_ReplaceMissingFilter

            ReplaceMissingValues m_ReplaceMissingFilter

        replace missing values in training instances

  - ### Class weka.clusterers.FilteredClusterer

    class FilteredClusterer extends SingleClustererEnhancer implements Serializable
    serialVersionUID:
      1420005943163412943L

    - #### Serialized Fields

      - ##### m_Filter

            Filter m_Filter

        The filter.

      - ##### m_FilteredInstances

            Instances m_FilteredInstances

        The instance structure of the filtered instances.

  - ### Class weka.clusterers.HierarchicalClusterer

    class HierarchicalClusterer extends AbstractClusterer implements Serializable
    serialVersionUID:
      1L

    - #### Serialized Fields

      - ##### m_bDistanceIsBranchLength

            boolean m_bDistanceIsBranchLength

        Whether the distance represent node height (if false) or branch length (if true).

      - ##### m_bPrintNewick

            boolean m_bPrintNewick

      - ##### m_clusters

            weka.clusterers.HierarchicalClusterer.Node[] m_clusters

      - ##### m_DistanceFunction

            DistanceFunction m_DistanceFunction

        distance function used for comparing members of a cluster

      - ##### m_instances

            Instances m_instances

        training data

      - ##### m_nClusterNr

            int[] m_nClusterNr

      - ##### m_nLinkType

            int m_nLinkType

        Holds the Link type used calculate distance between clusters

      - ##### m_nNumClusters

            int m_nNumClusters

        number of clusters desired in clustering

  - ### Class weka.clusterers.MakeDensityBasedClusterer

    class MakeDensityBasedClusterer extends AbstractDensityBasedClusterer implements Serializable
    serialVersionUID:
      -5643302427972186631L

    - #### Serialized Fields

      - ##### m_minStdDev

            double m_minStdDev

        default minimum standard deviation

      - ##### m_model

            DiscreteEstimator[][] m_model

        discrete distributions fitted to each discrete attribute in each cluster

      - ##### m_modelNormal

            double[][][] m_modelNormal

        normal distributions fitted to each numeric attribute in each cluster

      - ##### m_priors

            double[] m_priors

        prior probabilities for the fitted clusters

      - ##### m_replaceMissing

            ReplaceMissingValues m_replaceMissing

        globally replace missing values

      - ##### m_theInstances

            Instances m_theInstances

        holds training instances header information

      - ##### m_wrappedClusterer

            Clusterer m_wrappedClusterer

        The clusterer being wrapped

  - ### Class weka.clusterers.RandomizableClusterer

    class RandomizableClusterer extends AbstractClusterer implements Serializable
    serialVersionUID:
      -4819590778152242745L

    - #### Serialized Fields

      - ##### m_Seed

            int m_Seed

        The random number seed.

      - ##### m_SeedDefault

            int m_SeedDefault

        the default seed value

  - ### Class weka.clusterers.RandomizableDensityBasedClusterer

    class RandomizableDensityBasedClusterer extends AbstractDensityBasedClusterer implements Serializable
    serialVersionUID:
      -5325270357918932849L

    - #### Serialized Fields

      - ##### m_Seed

            int m_Seed

        The random number seed.

      - ##### m_SeedDefault

            int m_SeedDefault

        the default seed value

  - ### Class weka.clusterers.RandomizableSingleClustererEnhancer

    class RandomizableSingleClustererEnhancer extends AbstractClusterer implements Serializable
    serialVersionUID:
      -644847037106316249L

    - #### Serialized Fields

      - ##### m_Seed

            int m_Seed

        The random number seed.

      - ##### m_SeedDefault

            int m_SeedDefault

        the default seed value

  - ### Class weka.clusterers.SimpleKMeans

    class SimpleKMeans extends RandomizableClusterer implements Serializable
    serialVersionUID:
      -3235809600124455376L

    - #### Serialized Fields

      - ##### m_Assignments

            int[] m_Assignments

        Assignments obtained.

      - ##### m_canopyClusters

            Canopy m_canopyClusters

        The canopy clusterer (if being used)

      - ##### m_centroidCanopyAssignments

            List<long[]> m_centroidCanopyAssignments

        Canopies that each centroid falls into (determined by T1 radius)

      - ##### m_ClusterCentroids

            Instances m_ClusterCentroids

        holds the cluster centroids.

      - ##### m_ClusterMissingCounts

            double[][] m_ClusterMissingCounts

      - ##### m_ClusterNominalCounts

            double[][][] m_ClusterNominalCounts

        For each cluster, holds the frequency counts for the values of each nominal attribute.

      - ##### m_ClusterSizes

            double[] m_ClusterSizes

        The number of instances in each cluster.

      - ##### m_ClusterStdDevs

            Instances m_ClusterStdDevs

        Holds the standard deviations of the numeric attributes in each cluster.

      - ##### m_completed

            int m_completed

      - ##### m_dataPointCanopyAssignments

            List<long[]> m_dataPointCanopyAssignments

        Canopies that each training instance falls into (determined by T1 radius)

      - ##### m_displayStdDevs

            boolean m_displayStdDevs

        Display standard deviations for numeric atts.

      - ##### m_DistanceFunction

            DistanceFunction m_DistanceFunction

        the distance function used.

      - ##### m_dontReplaceMissing

            boolean m_dontReplaceMissing

        Replace missing values globally?

      - ##### m_executionSlots

            int m_executionSlots

        Number of threads to run

      - ##### m_failed

            int m_failed

      - ##### m_FastDistanceCalc

            boolean m_FastDistanceCalc

        whether to use fast calculation of distances (using a cut-off).

      - ##### m_FullMeansOrMediansOrModes

            double[] m_FullMeansOrMediansOrModes

        Stats on the full data set for comparison purposes. In case the attribute is numeric the value is the mean if is being used the Euclidian distance or the median if Manhattan distance and if the attribute is nominal then it's mode is saved.

      - ##### m_FullMissingCounts

            double[] m_FullMissingCounts

      - ##### m_FullNominalCounts

            double[][] m_FullNominalCounts

      - ##### m_FullStdDevs

            double[] m_FullStdDevs

      - ##### m_initializationMethod

            int m_initializationMethod

        The initialization method to use

      - ##### m_initialStartPoints

            Instances m_initialStartPoints

        Holds the initial start points, as supplied by the initialization method used

      - ##### m_Iterations

            int m_Iterations

        Keep track of the number of iterations completed before convergence.

      - ##### m_maxCanopyCandidates

            int m_maxCanopyCandidates

        The maximum number of candidate canopies to hold in memory at any one time (if using canopy clustering)

      - ##### m_MaxIterations

            int m_MaxIterations

        Maximum number of iterations to be executed.

      - ##### m_minClusterDensity

            double m_minClusterDensity

        The minimum cluster density (according to T2 distance) allowed. Used when periodically pruning candidate canopies (if using canopy clustering)

      - ##### m_NumClusters

            int m_NumClusters

        number of clusters to generate.

      - ##### m_periodicPruningRate

            int m_periodicPruningRate

        Prune low-density candidate canopies after every x instances have been seen (if using canopy clustering)

      - ##### m_PreserveOrder

            boolean m_PreserveOrder

        Preserve order of instances.

      - ##### m_ReplaceMissingFilter

            ReplaceMissingValues m_ReplaceMissingFilter

        replace missing values in training instances.

      - ##### m_speedUpDistanceCompWithCanopies

            boolean m_speedUpDistanceCompWithCanopies

        Whether to reducet the number of distance calcs done by k-means with canopies

      - ##### m_squaredErrors

            double[] m_squaredErrors

        Holds the squared errors for all clusters.

      - ##### m_t1

            double m_t1

        The t1 radius to pass through to Canopy

      - ##### m_t2

            double m_t2

        The t2 radius to pass through to Canopy

  - ### Class weka.clusterers.SingleClustererEnhancer

    class SingleClustererEnhancer extends AbstractClusterer implements Serializable
    serialVersionUID:
      4893928362926428671L

    - #### Serialized Fields

      - ##### m_Clusterer

            Clusterer m_Clusterer

        the clusterer

- ## Package weka.core

  - ### Class weka.core.AbstractInstance

    class AbstractInstance extends Object implements Serializable
    serialVersionUID:
      1482635194499365155L

    - #### Serialized Fields

      - ##### m_AttValues

            double[] m_AttValues

        The instance's attribute values.

      - ##### m_Dataset

            Instances m_Dataset

        The dataset the instance has access to. Null if the instance doesn't have access to any dataset. Only if an instance has access to a dataset, it knows about the actual attribute types.

      - ##### m_Weight

            double m_Weight

        The instance's weight.

  - ### Class weka.core.AlgVector

    class AlgVector extends Object implements Serializable
    serialVersionUID:
      -4023736016850256591L

    - #### Serialized Fields

      - ##### m_Elements

            double[] m_Elements

        The values of the matrix

  - ### Class weka.core.Attribute

    class Attribute extends Object implements Serializable
    serialVersionUID:
      -742180568732916383L

    - #### Serialized Fields

      - ##### m_AttributeInfo

            weka.core.AttributeInfo m_AttributeInfo

        The attribute info (null for numeric attributes)

      - ##### m_AttributeMetaInfo

            AttributeMetaInfo m_AttributeMetaInfo

        The meta data for the attribute.

      - ##### m_Index

            int m_Index

        The attribute's index.

      - ##### m_Name

            String m_Name

        The attribute's name.

      - ##### m_Type

            int m_Type

        The attribute's type.

      - ##### m_Weight

            double m_Weight

        The attribute's weight.

  - ### Class weka.core.AttributeLocator

    class AttributeLocator extends Object implements Serializable
    serialVersionUID:
      -2932848827681070345L

    - #### Serialized Fields

      - ##### m_AllowedIndices

            int[] m_AllowedIndices

        the attribute indices that may be inspected

      - ##### m_Attributes

            BitSet m_Attributes

        contains the attribute locations, either true or false Boolean objects

      - ##### m_Data

            Instances m_Data

        the referenced data

      - ##### m_Indices

            int[] m_Indices

        the indices

      - ##### m_LocatorIndices

            int[] m_LocatorIndices

        the indices of locator objects

      - ##### m_Locators

            ArrayList<AttributeLocator> m_Locators

        contains the locator locations, either null or a AttributeLocator reference

      - ##### m_Type

            int m_Type

        the type of the attribute

  - ### Class weka.core.AttributeMetaInfo

    class AttributeMetaInfo extends Object implements Serializable

    - #### Serialized Fields

      - ##### m_HasZeropoint

            boolean m_HasZeropoint

        Whether the attribute has a zeropoint.

      - ##### m_IsAveragable

            boolean m_IsAveragable

        Whether the attribute is averagable.

      - ##### m_IsRegular

            boolean m_IsRegular

        Whether the attribute is regular.

      - ##### m_LowerBound

            double m_LowerBound

        The attribute's lower numeric bound.

      - ##### m_LowerBoundIsOpen

            boolean m_LowerBoundIsOpen

        Whether the lower bound is open.

      - ##### m_Metadata

            ProtectedProperties m_Metadata

        The attribute's metadata.

      - ##### m_Ordering

            int m_Ordering

        The attribute's ordering.

      - ##### m_UpperBound

            double m_UpperBound

        The attribute's upper numeric bound.

      - ##### m_UpperBoundIsOpen

            boolean m_UpperBoundIsOpen

        Whether the upper bound is open

  - ### Class weka.core.AttributeStats

    class AttributeStats extends Object implements Serializable
    serialVersionUID:
      4434688832743939380L

    - #### Serialized Fields

      - ##### distinctCount

            int distinctCount

        The number of distinct values

      - ##### intCount

            int intCount

        The number of int-like values

      - ##### missingCount

            int missingCount

        The number of missing values

      - ##### nominalCounts

            int[] nominalCounts

        Counts of each nominal value

      - ##### nominalWeights

            double[] nominalWeights

        Weight mass for each nominal value

      - ##### numericStats

            Stats numericStats

        Stats on numeric value distributions

      - ##### realCount

            int realCount

        The number of real-like values (i.e. have a fractional part)

      - ##### totalCount

            int totalCount

        The total number of values (i.e. number of instances)

      - ##### uniqueCount

            int uniqueCount

        The number of values that only appear once

  - ### Class weka.core.BinarySparseInstance

    class BinarySparseInstance extends SparseInstance implements Serializable
    serialVersionUID:
      -5297388762342528737L

  - ### Class weka.core.Capabilities

    class Capabilities extends Object implements Serializable
    serialVersionUID:
      -5478590032325567849L

    - #### Serialized Fields

      - ##### m_AttributeTest

            boolean m_AttributeTest

        whether to perform attribute based tests

      - ##### m_Capabilities

            HashSet<Capabilities.Capability> m_Capabilities

        the hashset for storing the active capabilities

      - ##### m_Dependencies

            HashSet<Capabilities.Capability> m_Dependencies

        the hashset for storing dependent capabilities, eg for meta-classifiers

      - ##### m_FailReason

            Exception m_FailReason

        the reason why the test failed, used to throw an exception

      - ##### m_InstancesTest

            boolean m_InstancesTest

        whether to perform data based tests

      - ##### m_InterfaceDefinedCapabilities

            HashSet<Class> m_InterfaceDefinedCapabilities

        the interface-defined capabilities

      - ##### m_MinimumNumberInstances

            int m_MinimumNumberInstances

        the minimum number of instances in a dataset

      - ##### m_MinimumNumberInstancesTest

            boolean m_MinimumNumberInstancesTest

        whether to test for minimum number of instances

      - ##### m_MissingClassValuesTest

            boolean m_MissingClassValuesTest

        whether to test for missing class values

      - ##### m_MissingValuesTest

            boolean m_MissingValuesTest

        whether to test for missing values

      - ##### m_Owner

            CapabilitiesHandler m_Owner

        the object that owns this capabilities instance

      - ##### m_Test

            boolean m_Test

        whether to perform any tests at all

  - ### Class weka.core.ChebyshevDistance

    class ChebyshevDistance extends NormalizableDistance implements Serializable
    serialVersionUID:
      -7739904999895461429L

  - ### Class weka.core.DateAttributeInfo

    class DateAttributeInfo extends Object implements Serializable

    - #### Serialized Fields

      - ##### m_DateFormat

            SimpleDateFormat m_DateFormat

        Date format specification for date attributes

  - ### Class weka.core.Debug

    class Debug extends Object implements Serializable
    serialVersionUID:
      66171861743328020L

    - #### Serialized Fields

      - ##### m_Clock

            Debug.Clock m_Clock

        for clocking

      - ##### m_Enabled

            boolean m_Enabled

        whether logging is enabled

      - ##### m_Log

            Debug.Log m_Log

        for logging

  - ### Class weka.core.Debug.Clock

    class Clock extends Object implements Serializable
    serialVersionUID:
      4622161807307942201L

    - #### Serialized Fields

      - ##### m_CanMeasureCpuTime

            boolean m_CanMeasureCpuTime

        whether the system can measure the CPU time

      - ##### m_OutputFormat

            int m_OutputFormat

        the format of the output

      - ##### m_Running

            boolean m_Running

        whether the time is still clocked

      - ##### m_Start

            long m_Start

        the start time

      - ##### m_Stop

            long m_Stop

        the end time

      - ##### m_ThreadID

            long m_ThreadID

        the thread ID

      - ##### m_UseCpuTime

            boolean m_UseCpuTime

        whether to use the CPU time (by default TRUE)

  - ### Class weka.core.Debug.DBO

    class DBO extends Object implements Serializable
    serialVersionUID:
      -5245628124742606784L

    - #### Serialized Fields

      - ##### m_outputTypes

            Range m_outputTypes

        range of outputtyp

      - ##### m_verboseOn

            boolean m_verboseOn

        enables/disables output of debug information

  - ### Class weka.core.Debug.Log

    class Log extends Object implements Serializable
    serialVersionUID:
      1458435732111675823L

    - #### Serialized Fields

      - ##### m_Filename

            String m_Filename

        the filename, if any

      - ##### m_LoggerInitFailed

            boolean m_LoggerInitFailed

        whether the initialization of the logger failed

      - ##### m_NumFiles

            int m_NumFiles

        the number of files for rotating the logs

      - ##### m_Size

            int m_Size

        the size of the file (in bytes)

  - ### Class weka.core.Debug.Random

    class Random extends Random implements Serializable
    serialVersionUID:
      1256846887618333956L

    - #### Serialized Fields

      - ##### m_Debug

            boolean m_Debug

        whether to output debug information

      - ##### m_ID

            long m_ID

        the unique ID for this number generator

      - ##### m_Log

            Debug.Log m_Log

        the log to use for outputting the data, otherwise just stdout

  - ### Class weka.core.Debug.SimpleLog

    class SimpleLog extends Object implements Serializable
    serialVersionUID:
      -2671928223819510830L

    - #### Serialized Fields

      - ##### m_Filename

            String m_Filename

        the file to write to (if null then only stdout is used)

  - ### Class weka.core.Debug.Timestamp

    class Timestamp extends Object implements Serializable
    serialVersionUID:
      -6099868388466922753L

    - #### Serialized Fields

      - ##### m_Format

            String m_Format

        the format of the timestamp

      - ##### m_Formatter

            SimpleDateFormat m_Formatter

        handles the format of the output

      - ##### m_Stamp

            Date m_Stamp

        the actual date

  - ### Class weka.core.Defaults

    class Defaults extends Object implements Serializable
    serialVersionUID:
      1061521489520308096L

    - #### Serialized Fields

      - ##### m_defaults

            Map<Settings.SettingKey,Object> m_defaults

        Maintains the list of default settings

      - ##### m_defaultsID

            String m_defaultsID

        Identifier for this set of defaults

  - ### Class weka.core.DenseInstance

    class DenseInstance extends AbstractInstance implements Serializable
    serialVersionUID:
      1482635194499365122L

  - ### Class weka.core.DictionaryBuilder

    class DictionaryBuilder extends Object implements Serializable
    serialVersionUID:
      5579506627960356012L

    - #### Serialized Fields

      - ##### m_avgDocLength

            double m_avgDocLength

        The average document length

      - ##### m_classIndex

            int m_classIndex

        Holds the class index

      - ##### m_consolidatedDict

            Map<String,int[]> m_consolidatedDict

        Holds the final dictionary that is consolidated across classes and pruned according to m_wordsToKeep. First element of array contains the index of the word. The second (optional) element contains the document count for the word (i.e. number of training docs the word occurs in).

      - ##### m_count

            int m_count

        Count of input vectors seen

      - ##### m_dictsPerClass

            Map<String,int[]>[] m_dictsPerClass

        Holds the dictionaries (one per class) that are compiled while processing

      - ##### m_docLengthSum

            double m_docLengthSum

        The sum of document lengths

      - ##### m_doNotOperateOnPerClassBasis

            boolean m_doNotOperateOnPerClassBasis

        True if the final number of words to keep should not be applied on a per class basis

      - ##### m_IDFTransform

            boolean m_IDFTransform

        True if the IDF transform is to be applied

      - ##### m_inputContainsStringAttributes

            boolean m_inputContainsStringAttributes

        True if the input data contains string attributes to convert

      - ##### m_inputFormat

            Instances m_inputFormat

        Input structure

      - ##### m_lowerCaseTokens

            boolean m_lowerCaseTokens

        True if all tokens should be downcased.

      - ##### m_minFrequency

            int m_minFrequency

        Minimum frequency to retain dictionary entries

      - ##### m_normalize

            boolean m_normalize

        Whether to normalize to average length of training docs

      - ##### m_numClasses

            int m_numClasses

        Number of classes

      - ##### m_outputCounts

            boolean m_outputCounts

        Whether to output frequency counts instead of presence indicators

      - ##### m_outputFormat

            Instances m_outputFormat

        Output structure

      - ##### m_periodicPruneRate

            long m_periodicPruneRate

        Prune dictionary (per class) of low freq terms after every x documents. 0 = no periodic pruning

      - ##### m_Prefix

            String m_Prefix

        A String prefix for the attribute names.

      - ##### m_selectedRange

            Range m_selectedRange

        Range of columns to convert to word vectors.

      - ##### m_sortDictionary

            boolean m_sortDictionary

        Whether to keep the dictionary(s) sorted alphabetically

      - ##### m_stemmer

            Stemmer m_stemmer

        the stemming algorithm.

      - ##### m_stopwordsHandler

            StopwordsHandler m_stopwordsHandler

        Stopword handler to use.

      - ##### m_TFTransform

            boolean m_TFTransform

        True if the TF transform is to be applied

      - ##### m_tokenizer

            Tokenizer m_tokenizer

        the tokenizer algorithm to use.

      - ##### m_wordsToKeep

            int m_wordsToKeep

        The default number of words (per class if there is a class attribute assigned) to attempt to keep.

  - ### Class weka.core.EnvironmentProperties

    class EnvironmentProperties extends Properties implements Serializable

  - ### Class weka.core.EuclideanDistance

    class EuclideanDistance extends NormalizableDistance implements Serializable
    serialVersionUID:
      1068606253458807903L

  - ### Class weka.core.FastVector

    class FastVector extends ArrayList<E> implements Serializable
    serialVersionUID:
      -2173635135622930169L

  - ### Class weka.core.FilteredDistance

    class FilteredDistance extends Object implements Serializable

    - #### Serialized Fields

      - ##### m_Distance

            DistanceFunction m_Distance

        The distance function to use.

      - ##### m_Filter

            Filter m_Filter

        The filter to use.

      - ##### m_Remove

            Remove m_Remove

        Remove filter to remove attributes if required.

  - ### Class weka.core.InstanceComparator

    class InstanceComparator extends Object implements Serializable
    serialVersionUID:
      -6589278678230949683L

    - #### Serialized Fields

      - ##### m_IncludeClass

            boolean m_IncludeClass

        whether to include the class in the comparison

      - ##### m_Range

            Range m_Range

        the range of attributes to use for comparison.

  - ### Class weka.core.Instances

    class Instances extends AbstractList<Instance> implements Serializable
    serialVersionUID:
      -19412345060742748L

    - #### Serialized Fields

      - ##### m_Attributes

            ArrayList<Attribute> m_Attributes

        The attribute information.

      - ##### m_ClassIndex

            int m_ClassIndex

        The class attribute's index

      - ##### m_Instances

            ArrayList<Instance> m_Instances

        The instances.

      - ##### m_Lines

            int m_Lines

        The lines read so far in case of incremental loading. Since the StreamTokenizer will be re-initialized with every instance that is read, we have to keep track of the number of lines read so far.
        See Also:
          - `Instances.readInstance(Reader)`

      - ##### m_NamesToAttributeIndices

            HashMap<String,Integer> m_NamesToAttributeIndices

        A map to quickly find attribute indices based on their names.

      - ##### m_RelationName

            String m_RelationName

        The dataset's name.

  - ### Class weka.core.ManhattanDistance

    class ManhattanDistance extends NormalizableDistance implements Serializable
    serialVersionUID:
      6783782554224000243L

  - ### Class weka.core.Matrix

    class Matrix extends Object implements Serializable
    serialVersionUID:
      -3604757095849145838L

    - #### Serialized Fields

      - ##### m_Matrix

            Matrix m_Matrix

        Deprecated.
        The actual matrix

  - ### Class weka.core.MinkowskiDistance

    class MinkowskiDistance extends NormalizableDistance implements Serializable
    serialVersionUID:
      -7446019339455453893L

    - #### Serialized Fields

      - ##### m_Order

            double m_Order

        the order of the minkowski distance.

  - ### Class weka.core.NominalAttributeInfo

    class NominalAttributeInfo extends Object implements Serializable

    - #### Serialized Fields

      - ##### m_Hashtable

            Hashtable<Object,Integer> m_Hashtable

        Mapping of values to indices.

      - ##### m_Values

            ArrayList<Object> m_Values

        The attribute's values.

  - ### Class weka.core.NormalizableDistance

    class NormalizableDistance extends Object implements Serializable
    serialVersionUID:
      -2806520224161351708L

    - #### Serialized Fields

      - ##### m_ActiveIndices

            boolean[] m_ActiveIndices

        The boolean flags, whether an attribute will be used or not.

      - ##### m_AttributeIndices

            Range m_AttributeIndices

        The range of attributes to use for calculating the distance.

      - ##### m_Data

            Instances m_Data

        the instances used internally.

      - ##### m_DontNormalize

            boolean m_DontNormalize

        True if normalization is turned off (default false).

      - ##### m_Ranges

            double[][] m_Ranges

        The range of the attributes.

      - ##### m_Validated

            boolean m_Validated

        Whether all the necessary preparations have been done.

  - ### Exception weka.core.NoSupportForMissingValuesException

    class NoSupportForMissingValuesException extends WekaException implements Serializable
    serialVersionUID:
      5161175307725893973L

  - ### Class weka.core.ProtectedProperties

    class ProtectedProperties extends Properties implements Serializable
    serialVersionUID:
      3876658672657323985L

    - #### Serialized Fields

      - ##### closed

            boolean closed

        the properties need to be open during construction of the object

  - ### Class weka.core.Queue

    class Queue extends Object implements Serializable
    serialVersionUID:
      -1141282001146389780L

    - #### Serialized Fields

      - ##### m_Head

            weka.core.Queue.QueueNode m_Head

        Store a reference to the head of the queue

      - ##### m_Size

            int m_Size

        Store the c m_Tail.m_Nexturrent number of elements in the queue

      - ##### m_Tail

            weka.core.Queue.QueueNode m_Tail

        Store a reference to the tail of the queue

  - ### Class weka.core.Queue.QueueNode

    class QueueNode extends Object implements Serializable
    serialVersionUID:
      -5119358279412097455L

    - #### Serialized Fields

      - ##### m_Contents

            Object m_Contents

        The nodes contents

      - ##### m_Next

            weka.core.Queue.QueueNode m_Next

        The next node in the queue

  - ### Class weka.core.RandomVariates

    class RandomVariates extends Random implements Serializable
    serialVersionUID:
      -4763742718209460354L

  - ### Class weka.core.Range

    class Range extends Object implements Serializable
    serialVersionUID:
      3667337062176835900L

    - #### Serialized Fields

      - ##### m_Invert

            boolean m_Invert

        Whether matching should be inverted.

      - ##### m_RangeStrings

            ArrayList<String> m_RangeStrings

        Record the string representations of the columns to delete.

      - ##### m_SelectFlags

            boolean[] m_SelectFlags

        The array of flags for whether an column is selected.

      - ##### m_Upper

            int m_Upper

        Store the maximum value permitted in the range. -1 indicates that no upper value has been set

  - ### Class weka.core.RelationalAttributeInfo

    class RelationalAttributeInfo extends NominalAttributeInfo implements Serializable

    - #### Serialized Fields

      - ##### m_Header

            Instances m_Header

        The header information for a relation-valued attribute.

  - ### Class weka.core.RelationalLocator

    class RelationalLocator extends AttributeLocator implements Serializable
    serialVersionUID:
      4646872277151854732L

  - ### Class weka.core.SelectedTag

    class SelectedTag extends Object implements Serializable
    serialVersionUID:
      6947341624626504975L

    - #### Serialized Fields

      - ##### m_Selected

            int m_Selected

        The index of the selected tag

      - ##### m_Tags

            Tag[] m_Tags

        The set of tags to choose from

  - ### Class weka.core.SerializedObject

    class SerializedObject extends Object implements Serializable
    serialVersionUID:
      6635502953928860434L

    - #### Serialized Fields

      - ##### m_isCompressed

            boolean m_isCompressed

        Whether or not the object is compressed.

      - ##### m_isJython

            boolean m_isJython

        Whether it is a Jython object or not

      - ##### m_storedObjectArray

            byte[] m_storedObjectArray

        The array storing the object.

  - ### Class weka.core.Settings

    class Settings extends Object implements Serializable
    serialVersionUID:
      -4005372566372478008L

    - #### Serialized Fields

      - ##### m_ID

            String m_ID

        The name of the entry within the store to save to

      - ##### m_settings

            Map<String,Map<Settings.SettingKey,Object>> m_settings

        outer map keyed by perspective ID. Inner map - settings for a perspective.

      - ##### m_storeName

            String m_storeName

        The name of the store that these settings should be saved/loaded to/from

  - ### Class weka.core.Settings.SettingKey

    class SettingKey extends Object implements Serializable

    - #### Serialized Fields

      - ##### m_description

            String m_description

        Description/display name of the seting

      - ##### m_key

            String m_key

        Key for this setting

      - ##### m_meta

            Map<String,String> m_meta

        Metadata for this setting - e.g. file property could specify whether it is files only, directories only or both

      - ##### m_pickList

            List<String> m_pickList

        Pick list (can be null if not applicable) for a string-based setting

      - ##### m_toolTip

            String m_toolTip

        Tool tip for the setting

  - ### Class weka.core.SingleIndex

    class SingleIndex extends Object implements Serializable
    serialVersionUID:
      5285169134430839303L

    - #### Serialized Fields

      - ##### m_IndexString

            String m_IndexString

        Record the string representation of the number.

      - ##### m_SelectedIndex

            int m_SelectedIndex

        The selected index.

      - ##### m_Upper

            int m_Upper

        Store the maximum value permitted. -1 indicates that no upper value has been set

  - ### Class weka.core.SparseInstance

    class SparseInstance extends AbstractInstance implements Serializable
    serialVersionUID:
      -3579051291332630149L

    - #### Serialized Fields

      - ##### m_Indices

            int[] m_Indices

        The index of the attribute associated with each stored value.

      - ##### m_NumAttributes

            int m_NumAttributes

        The maximum number of values that can be stored.

  - ### Class weka.core.StringLocator

    class StringLocator extends AttributeLocator implements Serializable
    serialVersionUID:
      7805522230268783972L

  - ### Class weka.core.Tag

    class Tag extends Object implements Serializable
    serialVersionUID:
      3326379903447135320L

    - #### Serialized Fields

      - ##### m_ID

            int m_ID

        The ID

      - ##### m_IDStr

            String m_IDStr

        The unique string for this tag, doesn't have to be numeric

      - ##### m_Readable

            String m_Readable

        The descriptive text

  - ### Class weka.core.TestInstances

    class TestInstances extends Object implements Serializable
    serialVersionUID:
      -6263968936330390469L

    - #### Serialized Fields

      - ##### m_ClassIndex

            int m_ClassIndex

        the class index (-1 is LAST, -2 means no class)
        See Also:
          - `TestInstances.CLASS_IS_LAST`
          - `TestInstances.NO_CLASS`

      - ##### m_ClassType

            int m_ClassType

        the class type

      - ##### m_Data

            Instances m_Data

        the generated data

      - ##### m_Handler

            CapabilitiesHandler m_Handler

        the CapabilitiesHandler to get the Capabilities from

      - ##### m_MultiInstance

            boolean m_MultiInstance

        whether to generate Multi-Instance data or not

      - ##### m_NumClasses

            int m_NumClasses

        the number of classes (in case of NOMINAL class)

      - ##### m_NumDate

            int m_NumDate

        the number of date attributes

      - ##### m_NumInstances

            int m_NumInstances

        the number of instances

      - ##### m_NumInstancesRelational

            int m_NumInstancesRelational

        the number of instances in relational attributes (applies also for bags in multi-instance)

      - ##### m_NumNominal

            int m_NumNominal

        the number of nominal attributes

      - ##### m_NumNominalValues

            int m_NumNominalValues

        the number of values for nominal attributes

      - ##### m_NumNumeric

            int m_NumNumeric

        the number of numeric attributes

      - ##### m_NumRelational

            int m_NumRelational

        the number of relational attributes

      - ##### m_NumRelationalDate

            int m_NumRelationalDate

        the number of date attributes in a relational attribute

      - ##### m_NumRelationalNominal

            int m_NumRelationalNominal

        the number of nominal attributes in a relational attribute

      - ##### m_NumRelationalNominalValues

            int m_NumRelationalNominalValues

        the number of values for nominal attributes in relational attributes

      - ##### m_NumRelationalNumeric

            int m_NumRelationalNumeric

        the number of numeric attributes in a relational attribute

      - ##### m_NumRelationalString

            int m_NumRelationalString

        the number of string attributes in a relational attribute

      - ##### m_NumString

            int m_NumString

        the number of string attributes

      - ##### m_Random

            Random m_Random

        the random number generator

      - ##### m_Relation

            String m_Relation

        the name of the relation

      - ##### m_RelationalClassFormat

            Instances m_RelationalClassFormat

        the format of the multi-instance data of the class

      - ##### m_RelationalFormat

            Instances[] m_RelationalFormat

        the format of the multi-instance data

      - ##### m_Seed

            int m_Seed

        the seed value

      - ##### m_Words

            String[] m_Words

        for generating String attributes/classes

      - ##### m_WordSeparators

            String m_WordSeparators

        for generating String attributes/classes

  - ### Class weka.core.Trie

    class Trie extends Object implements Serializable
    serialVersionUID:
      -5897980928817779048L

    - #### Serialized Fields

      - ##### m_HashCode

            int m_HashCode

        the hash code

      - ##### m_RecalcHashCode

            boolean m_RecalcHashCode

        whether the structure got modified and the hash code needs to be re-calculated

      - ##### m_Root

            Trie.TrieNode m_Root

        the root node

  - ### Class weka.core.Trie.TrieNode

    class TrieNode extends DefaultMutableTreeNode implements Serializable
    serialVersionUID:
      -2252907099391881148L

    - #### Serialized Fields

      - ##### m_Children

            Hashtable<Character,Trie.TrieNode> m_Children

        for fast access to the children

  - ### Exception weka.core.UnassignedClassException

    class UnassignedClassException extends RuntimeException implements Serializable
    serialVersionUID:
      6268278694768818235L

  - ### Exception weka.core.UnassignedDatasetException

    class UnassignedDatasetException extends RuntimeException implements Serializable
    serialVersionUID:
      -9000116786626328854L

  - ### Exception weka.core.UnsupportedAttributeTypeException

    class UnsupportedAttributeTypeException extends WekaException implements Serializable
    serialVersionUID:
      2658987325328414838L

  - ### Exception weka.core.UnsupportedClassTypeException

    class UnsupportedClassTypeException extends WekaException implements Serializable
    serialVersionUID:
      5175741076972192151L

  - ### Exception weka.core.WekaException

    class WekaException extends Exception implements Serializable
    serialVersionUID:
      6428269989006208585L

- ## Package weka.core.converters

  - ### Class weka.core.converters.AbstractFileLoader

    class AbstractFileLoader extends AbstractLoader implements Serializable
    serialVersionUID:
      5535537461920594758L

    - #### Serialized Fields

      - ##### m_File

            String m_File

        the file

      - ##### m_sourceFile

            File m_sourceFile

        Holds the source of the data set.

      - ##### m_useRelativePath

            boolean m_useRelativePath

        use relative file paths

  - ### Class weka.core.converters.AbstractFileSaver

    class AbstractFileSaver extends AbstractSaver implements Serializable
    serialVersionUID:
      2399441762235754491L

    - #### Serialized Fields

      - ##### FILE_EXTENSION

            String FILE_EXTENSION

        The file extension of the destination file.

      - ##### FILE_EXTENSION_COMPRESSED

            String FILE_EXTENSION_COMPRESSED

        the extension for compressed files

      - ##### m_dir

            String m_dir

        The directory of the file (chosen in the GUI).

      - ##### m_incrementalCounter

            int m_incrementalCounter

        Counter. In incremental mode after reading 100 instances they will be written to a file.

      - ##### m_outputFile

            File m_outputFile

        The destination file.

      - ##### m_prefix

            String m_prefix

        The prefix for the filename (chosen in the GUI).

      - ##### m_useRelativePath

            boolean m_useRelativePath

        use relative file paths

  - ### Class weka.core.converters.AbstractLoader

    class AbstractLoader extends Object implements Serializable
    serialVersionUID:
      2425432084900694551L

    - #### Serialized Fields

      - ##### m_retrieval

            int m_retrieval

        The current retrieval mode

  - ### Class weka.core.converters.AbstractSaver

    class AbstractSaver extends Object implements Serializable
    serialVersionUID:
      -27467499727819258L

    - #### Serialized Fields

      - ##### m_DoNotCheckCapabilities

            boolean m_DoNotCheckCapabilities

        Whether capabilities should not be checked

      - ##### m_instances

            Instances m_instances

        The instances that should be stored

      - ##### m_retrieval

            int m_retrieval

        The current retrieval mode

      - ##### m_writeMode

            int m_writeMode

        The current write mode

  - ### Class weka.core.converters.ArffLoader

    class ArffLoader extends AbstractFileLoader implements Serializable
    serialVersionUID:
      2726929550544048587L

    - #### Serialized Fields

      - ##### m_retainStringVals

            boolean m_retainStringVals

        Whether the values of string attributes should be retained in memory when reading incrementally

      - ##### m_URL

            String m_URL

        the url

  - ### Class weka.core.converters.ArffSaver

    class ArffSaver extends AbstractFileSaver implements Serializable
    serialVersionUID:
      2223634248900042228L

    - #### Serialized Fields

      - ##### m_CompressOutput

            boolean m_CompressOutput

        whether to compress the output

      - ##### m_MaxDecimalPlaces

            int m_MaxDecimalPlaces

        Max number of decimal places for numeric values

  - ### Class weka.core.converters.C45Loader

    class C45Loader extends AbstractFileLoader implements Serializable
    serialVersionUID:
      5454329403218219L

    - #### Serialized Fields

      - ##### m_fileStem

            String m_fileStem

        Holds the filestem.

      - ##### m_ignore

            boolean[] m_ignore

        Which attributes are ignore or label. These are *not* included in the arff representation.

      - ##### m_numAttribs

            int m_numAttribs

        Number of attributes in the data (including ignore and label attributes).

      - ##### m_sourceFileData

            File m_sourceFileData

        Describe variable `m_sourceFileData` here.

  - ### Class weka.core.converters.C45Saver

    class C45Saver extends AbstractFileSaver implements Serializable
    serialVersionUID:
      -821428878384253377L

  - ### Class weka.core.converters.ConverterUtils

    class ConverterUtils extends Object implements Serializable
    serialVersionUID:
      -2460855349276148760L

  - ### Class weka.core.converters.ConverterUtils.DataSink

    class DataSink extends Object implements Serializable
    serialVersionUID:
      -1504966891136411204L

    - #### Serialized Fields

      - ##### m_Saver

            Saver m_Saver

        the saver to use for storing the data.

      - ##### m_Stream

            OutputStream m_Stream

        the stream to store the data in (always in ARFF format).

  - ### Class weka.core.converters.ConverterUtils.DataSource

    class DataSource extends Object implements Serializable
    serialVersionUID:
      -613122395928757332L

    - #### Serialized Fields

      - ##### m_BatchBuffer

            Instances m_BatchBuffer

        the batch buffer.

      - ##### m_BatchCounter

            int m_BatchCounter

        the instance counter for the batch case.

      - ##### m_File

            File m_File

        the file to load.

      - ##### m_Incremental

            boolean m_Incremental

        whether the loader is incremental.

      - ##### m_IncrementalBuffer

            Instance m_IncrementalBuffer

        the last internally read instance.

      - ##### m_Loader

            Loader m_Loader

        the loader.

      - ##### m_URL

            URL m_URL

        the URL to load.

  - ### Class weka.core.converters.CSVLoader

    class CSVLoader extends AbstractFileLoader implements Serializable
    serialVersionUID:
      -1300595850715808438L

    - #### Serialized Fields

      - ##### m_bufferSize

            int m_bufferSize

        The maximum number of rows to hold in memory at any one time

      - ##### m_current

            ArrayList<Object> m_current

      - ##### m_dateAttributes

            Range m_dateAttributes

        The range of attributes to force to type date

      - ##### m_dateFormat

            String m_dateFormat

        The formatting string to use to parse dates

      - ##### m_Enclosures

            String m_Enclosures

        enclosure character(s) to use for strings

      - ##### m_FieldSeparator

            String m_FieldSeparator

        the field separator.

      - ##### m_fieldSeparatorAndEnclosures

            String[] m_fieldSeparatorAndEnclosures

        Array holding field separator and enclosures to pass through to the underlying ArffReader

      - ##### m_formatter

            SimpleDateFormat m_formatter

        The formatter to use on dates

      - ##### m_incrementalReader

            ArffLoader.ArffReader m_incrementalReader

        Reader used to process and output data incrementally

      - ##### m_MissingValue

            String m_MissingValue

        The placeholder for missing values.

      - ##### m_noHeaderRow

            boolean m_noHeaderRow

        whether the csv file contains a header row with att names

      - ##### m_NominalAttributes

            Range m_NominalAttributes

        The range of attributes to force to type nominal.

      - ##### m_nominalLabelSpecs

            List<String> m_nominalLabelSpecs

        The user-supplied legal nominal values - each entry in the list is a spec

      - ##### m_nominalVals

            Map<Integer,LinkedHashSet<String>> m_nominalVals

        Lookup for nominal values

      - ##### m_numBufferedRows

            int m_numBufferedRows

      - ##### m_numericAttributes

            Range m_numericAttributes

        The range of attributes to force to type numeric

      - ##### m_rowBuffer

            List<String> m_rowBuffer

        The in memory row buffer

      - ##### m_StringAttributes

            Range m_StringAttributes

        The range of attributes to force to type string.

      - ##### m_types

            weka.core.converters.CSVLoader.TYPE[] m_types

  - ### Class weka.core.converters.CSVSaver

    class CSVSaver extends AbstractFileSaver implements Serializable
    serialVersionUID:
      476636654410701807L

    - #### Serialized Fields

      - ##### m_FieldSeparator

            String m_FieldSeparator

        the field separator.

      - ##### m_MaxDecimalPlaces

            int m_MaxDecimalPlaces

        Max number of decimal places for numeric values

      - ##### m_MissingValue

            String m_MissingValue

        The placeholder for missing values.

      - ##### m_noHeaderRow

            boolean m_noHeaderRow

        Set to true to not write the header row

  - ### Class weka.core.converters.DatabaseConnection

    class DatabaseConnection extends DatabaseUtils implements Serializable
    serialVersionUID:
      1673169848863178695L

  - ### Class weka.core.converters.DatabaseLoader

    class DatabaseLoader extends AbstractLoader implements Serializable
    serialVersionUID:
      -7936159015338318659L

    - #### Serialized Fields

      - ##### m_checkForTable

            boolean m_checkForTable

        If true it checks whether or not the table exists in the database before loading depending on jdbc metadata information. Set flag to false if no check is required or if jdbc metadata is not complete.

      - ##### m_choice

            int m_choice

        Decides which SQL statement to limit the number of rows should be used. DBMS dependent. Algorithm just tries several possibilities.

      - ##### m_counter

            int m_counter

        Indicates how many rows has already been loaded incrementally

      - ##### m_CreateSparseData

            boolean m_CreateSparseData

        Determines whether sparse data is created

      - ##### m_CustomPropsFile

            File m_CustomPropsFile

        the custom props file to use instead of default one.

      - ##### m_DataBaseConnection

            DatabaseConnection m_DataBaseConnection

        The database connection

      - ##### m_datasetPseudoInc

            Instances m_datasetPseudoInc

        Used in pseudoincremental mode. The whole dataset from which instances will be read incrementally.

      - ##### m_firstTime

            boolean m_firstTime

        Flag indicating that incremental process wants to read first instance

      - ##### m_idColumn

            String m_idColumn

        Name of the primary key column that will allow unique ordering necessary for incremental loading. The name is specified in the DatabaseUtils file.

      - ##### m_inc

            boolean m_inc

        Flag indicating that incremental mode is chosen (for command line use only)

      - ##### m_Keys

            String m_Keys

        the keys for unique ordering

      - ##### m_nominalIndexes

            Hashtable<String,Double>[] m_nominalIndexes

        Stores the index of a nominal value

      - ##### m_nominalStrings

            ArrayList<String>[] m_nominalStrings

        Stores the nominal value

      - ##### m_nominalToStringLimit

            int m_nominalToStringLimit

        Limit when an attribute is treated as string attribute and not as a nominal one because it has to many values.

      - ##### m_oldStructure

            Instances m_oldStructure

        Set of instances that equals m_structure except that the auto_generated_id column is not included as an attribute

      - ##### m_orderBy

            ArrayList<String> m_orderBy

        Contains the name of the columns that uniquely define a row in the ResultSet. Ensures a unique ordering of instances for indremental loading.

      - ##### m_Password

            String m_Password

        the database password to use

      - ##### m_pseudoIncremental

            boolean m_pseudoIncremental

        Flag indicating that pseudo incremental mode is used (all instances load at once into main memeory and then incrementally from main memory instead of the database)

      - ##### m_query

            String m_query

        The user defined query to load instances. (form: SELECT *|&ltcolumn-list> FROM &lttable> [WHERE <condition>])

      - ##### m_rowCount

            int m_rowCount

        The number of rows obtained by m_query, eg the size of the ResultSet to load

      - ##### m_structure

            Instances m_structure

        The header information that is retrieved in the beginning of incremental loading

      - ##### m_URL

            String m_URL

        the JDBC URL to use

      - ##### m_User

            String m_User

        the database user to use

  - ### Class weka.core.converters.DatabaseSaver

    class DatabaseSaver extends AbstractSaver implements Serializable
    serialVersionUID:
      863971733782624956L

    - #### Serialized Fields

      - ##### m_count

            int m_count

        counts the rows and used as a primary key value.

      - ##### m_createDate

            String m_createDate

        The database specific type for a date (read in from the properties file).

      - ##### m_createDouble

            String m_createDouble

        The database specific type for a double (read in from the properties file).

      - ##### m_createInt

            String m_createInt

        The database specific type for an int (read in from the properties file).

      - ##### m_createText

            String m_createText

        The database specific type for a string (read in from the properties file).

      - ##### m_CustomPropsFile

            File m_CustomPropsFile

        the custom props file to use instead of default one.

      - ##### m_DataBaseConnection

            DatabaseConnection m_DataBaseConnection

        The database connection.

      - ##### m_DateFormat

            SimpleDateFormat m_DateFormat

        For converting the date value into a database string.

      - ##### m_id

            boolean m_id

        Flag indicating if a primary key column should be added.

      - ##### m_idColumn

            String m_idColumn

        The name of the primary key column that will be automatically generated (if enabled). The name is read from DatabaseUtils.

      - ##### m_inputFile

            String m_inputFile

        An input arff file (for command line use).

      - ##### m_Password

            String m_Password

        the password for the database.

      - ##### m_resolvedTableName

            String m_resolvedTableName

        Table name with any environment variables resolved

      - ##### m_tableName

            String m_tableName

        The name of the table in which the instances should be stored.

      - ##### m_tabName

            boolean m_tabName

        Flag indicating whether the default name of the table is the relaion name or not.

      - ##### m_truncate

            boolean m_truncate

        Whether to truncate (i.e. drop and then recreate) the table if it already exists

      - ##### m_URL

            String m_URL

        the database URL.

      - ##### m_Username

            String m_Username

        the user name for the database.

  - ### Class weka.core.converters.DictionarySaver

    class DictionarySaver extends AbstractFileSaver implements Serializable
    serialVersionUID:
      -19891905988830722L

    - #### Serialized Fields

      - ##### m_dictionaryBuilder

            DictionaryBuilder m_dictionaryBuilder

        The dictionary builder to use

      - ##### m_dictionaryIsBinary

            boolean m_dictionaryIsBinary

        Whether the dictionary file contains a binary serialized dictionary, rather than plain text

      - ##### m_periodicPruningRate

            long m_periodicPruningRate

        Prune the dictionary every x instances. <=0 means no periodic pruning

  - ### Class weka.core.converters.JSONLoader

    class JSONLoader extends AbstractFileLoader implements Serializable
    serialVersionUID:
      3764533621135196582L

    - #### Serialized Fields

      - ##### m_JSON

            JSONNode m_JSON

        the loaded JSON object.

      - ##### m_URL

            String m_URL

        the url.

  - ### Class weka.core.converters.JSONSaver

    class JSONSaver extends AbstractFileSaver implements Serializable
    serialVersionUID:
      -1047134047244534557L

    - #### Serialized Fields

      - ##### m_ClassIndex

            SingleIndex m_ClassIndex

        the class index.

      - ##### m_CompressOutput

            boolean m_CompressOutput

        whether to compress the output.

  - ### Class weka.core.converters.LibSVMLoader

    class LibSVMLoader extends AbstractFileLoader implements Serializable
    serialVersionUID:
      4988360125354664417L

    - #### Serialized Fields

      - ##### m_Buffer

            Vector<double[]> m_Buffer

        the buffer of the rows read so far.

      - ##### m_URL

            String m_URL

        the url.

  - ### Class weka.core.converters.LibSVMSaver

    class LibSVMSaver extends AbstractFileSaver implements Serializable
    serialVersionUID:
      2792295817125694786L

    - #### Serialized Fields

      - ##### m_ClassIndex

            SingleIndex m_ClassIndex

        the class index

  - ### Exception weka.core.converters.Loader.StructureNotReadyException

    class StructureNotReadyException extends IOException implements Serializable
    serialVersionUID:
      1938493033987645828L

  - ### Class weka.core.converters.MatlabLoader

    class MatlabLoader extends AbstractFileLoader implements Serializable
    serialVersionUID:
      -8861142318612875251L

    - #### Serialized Fields

      - ##### m_Buffer

            Vector<Vector<Double>> m_Buffer

        the buffer of the rows read so far.

      - ##### m_URL

            String m_URL

        the url.

  - ### Class weka.core.converters.MatlabSaver

    class MatlabSaver extends AbstractFileSaver implements Serializable
    serialVersionUID:
      4118356803697172614L

    - #### Serialized Fields

      - ##### m_Format

            DecimalFormat m_Format

        for formatting the numbers.

      - ##### m_HeaderWritten

            boolean m_HeaderWritten

        whether the header was written already.

      - ##### m_UseDouble

            boolean m_UseDouble

        whether to save in double instead of single precision format.

      - ##### m_UseTabs

            boolean m_UseTabs

        whether to use tabs instead of blanks.

  - ### Class weka.core.converters.SerializedInstancesLoader

    class SerializedInstancesLoader extends AbstractFileLoader implements Serializable
    serialVersionUID:
      2391085836269030715L

    - #### Serialized Fields

      - ##### m_Dataset

            Instances m_Dataset

        Holds the structure (header) of the data set.

      - ##### m_IncrementalIndex

            int m_IncrementalIndex

        The current index position for incremental reading

  - ### Class weka.core.converters.SerializedInstancesSaver

    class SerializedInstancesSaver extends AbstractFileSaver implements Serializable
    serialVersionUID:
      -7717010648500658872L

    - #### Serialized Fields

      - ##### m_objectstream

            ObjectOutputStream m_objectstream

        the output stream.

  - ### Class weka.core.converters.StreamTokenizerUtils

    class StreamTokenizerUtils extends Object implements Serializable
    serialVersionUID:
      -5786996944597404253L

  - ### Class weka.core.converters.SVMLightLoader

    class SVMLightLoader extends AbstractFileLoader implements Serializable
    serialVersionUID:
      4988360125354664417L

    - #### Serialized Fields

      - ##### m_Buffer

            Vector<double[]> m_Buffer

        the buffer of the rows read so far.

      - ##### m_URL

            String m_URL

        the url.

  - ### Class weka.core.converters.SVMLightSaver

    class SVMLightSaver extends AbstractFileSaver implements Serializable
    serialVersionUID:
      2605714599263995835L

    - #### Serialized Fields

      - ##### m_ClassIndex

            SingleIndex m_ClassIndex

        the class index.

  - ### Class weka.core.converters.TextDirectoryLoader

    class TextDirectoryLoader extends AbstractLoader implements Serializable
    serialVersionUID:
      2592118773712247647L

    - #### Serialized Fields

      - ##### m_charSet

            String m_charSet

        The charset to use when loading text files (default is to just use the default charset).

      - ##### m_Debug

            boolean m_Debug

        whether to print some debug information

      - ##### m_filesByClass

            List<LinkedList<String>> m_filesByClass

      - ##### m_lastClassDir

            int m_lastClassDir

      - ##### m_OutputFilename

            boolean m_OutputFilename

        whether to include the filename as an extra attribute

      - ##### m_sourceFile

            File m_sourceFile

        Holds the source of the data set.

      - ##### m_structure

            Instances m_structure

        Holds the determined structure (header) of the data set.

  - ### Class weka.core.converters.XRFFLoader

    class XRFFLoader extends AbstractFileLoader implements Serializable
    serialVersionUID:
      3764533621135196582L

    - #### Serialized Fields

      - ##### m_URL

            String m_URL

        the url

      - ##### m_XMLInstances

            XMLInstances m_XMLInstances

        the loaded XML document

  - ### Class weka.core.converters.XRFFSaver

    class XRFFSaver extends AbstractFileSaver implements Serializable
    serialVersionUID:
      -7226404765213522043L

    - #### Serialized Fields

      - ##### m_ClassIndex

            SingleIndex m_ClassIndex

        the class index

      - ##### m_CompressOutput

            boolean m_CompressOutput

        whether to compress the output

      - ##### m_XMLInstances

            XMLInstances m_XMLInstances

        the generated XML document

- ## Package weka.core.expressionlanguage.common

  - ### Class weka.core.expressionlanguage.common.NoVariables

    class NoVariables extends Object implements Serializable

  - ### Class weka.core.expressionlanguage.common.Primitives

    class Primitives extends Object implements Serializable
    serialVersionUID:
      -6356635298310530223L

  - ### Class weka.core.expressionlanguage.common.Primitives.BooleanConstant

    class BooleanConstant extends Object implements Serializable
    serialVersionUID:
      -7104666336890622673L

    - #### Serialized Fields

      - ##### value

            boolean value

  - ### Class weka.core.expressionlanguage.common.Primitives.BooleanVariable

    class BooleanVariable extends Object implements Serializable
    serialVersionUID:
      6041670101306161521L

    - #### Serialized Fields

      - ##### name

            String name

      - ##### value

            boolean value

  - ### Class weka.core.expressionlanguage.common.Primitives.DoubleConstant

    class DoubleConstant extends Object implements Serializable
    serialVersionUID:
      6876724986473710563L

    - #### Serialized Fields

      - ##### value

            double value

  - ### Class weka.core.expressionlanguage.common.Primitives.DoubleVariable

    class DoubleVariable extends Object implements Serializable
    serialVersionUID:
      -6059066803856814750L

    - #### Serialized Fields

      - ##### name

            String name

      - ##### value

            double value

  - ### Class weka.core.expressionlanguage.common.Primitives.StringConstant

    class StringConstant extends Object implements Serializable
    serialVersionUID:
      491766938196527684L

    - #### Serialized Fields

      - ##### value

            String value

  - ### Class weka.core.expressionlanguage.common.Primitives.StringVariable

    class StringVariable extends Object implements Serializable
    serialVersionUID:
      -7332982581964981085L

    - #### Serialized Fields

      - ##### name

            String name

      - ##### value

            String value

  - ### Class weka.core.expressionlanguage.common.SimpleVariableDeclarations

    class SimpleVariableDeclarations extends Object implements Serializable

    - #### Serialized Fields

      - ##### initializer

            SimpleVariableDeclarations.VariableInitializer initializer

        the initializer to initialize the variables with values

      - ##### variables

            Map<String,Node> variables

        the variable declarations

  - ### Class weka.core.expressionlanguage.common.SimpleVariableDeclarations.VariableInitializer

    class VariableInitializer extends Object implements Serializable

    - #### Serialized Fields

      - ##### variables

            Map<String,Node> variables

        The variables that have been declared and used in a program

  - ### Class weka.core.expressionlanguage.common.VariableDeclarationsCompositor

    class VariableDeclarationsCompositor extends Object implements Serializable

    - #### Serialized Fields

      - ##### declarations

            VariableDeclarations[] declarations

        the declarations being combined

- ## Package weka.core.expressionlanguage.core

  - ### Exception weka.core.expressionlanguage.core.SemanticException

    class SemanticException extends Exception implements Serializable
    serialVersionUID:
      -1212116135142845573L

  - ### Exception weka.core.expressionlanguage.core.SyntaxException

    class SyntaxException extends Exception implements Serializable
    serialVersionUID:
      390076835893846782L

- ## Package weka.core.expressionlanguage.weka

  - ### Class weka.core.expressionlanguage.weka.InstancesHelper

    class InstancesHelper extends Object implements Serializable
    serialVersionUID:
      -4398876812339967703L

    - #### Serialized Fields

      - ##### dataRetained

            boolean dataRetained

        True if this instance retains the full dataset rather than just the attribute information

      - ##### dataset

            Instances dataset

        the dataset whose instance values should be exposed

      - ##### instance

            Instance instance

        the current instance whose values should be exposed

      - ##### missingAccessed

            boolean missingAccessed

        whether a missing value has been evaluated during computation

  - ### Class weka.core.expressionlanguage.weka.StatsHelper

    class StatsHelper extends Object implements Serializable

    - #### Serialized Fields

      - ##### stats

            Stats stats

      - ##### usedVariables

            Set<String> usedVariables

      - ##### variables

            Map<String,Node> variables

- ## Package weka.core.json

  - ### Class weka.core.json.JSONNode

    class JSONNode extends DefaultMutableTreeNode implements Serializable
    serialVersionUID:
      -3047440914507883491L

    - #### Serialized Fields

      - ##### m_Name

            String m_Name

        the name of the node.

      - ##### m_NodeType

            JSONNode.NodeType m_NodeType

        the type of the node.

      - ##### m_Value

            Object m_Value

        the value of the node.

- ## Package weka.core.matrix

  - ### Class weka.core.matrix.CholeskyDecomposition

    class CholeskyDecomposition extends Object implements Serializable
    serialVersionUID:
      -8739775942782694701L

    - #### Serialized Fields

      - ##### isspd

            boolean isspd

        Symmetric and positive definite flag.
        is symmetric and positive definite flag.

      - ##### L

            double[][] L

        Array for internal storage of decomposition.
        internal array storage.

      - ##### n

            int n

        Row and column dimension (square matrix).
        matrix dimension.

  - ### Class weka.core.matrix.EigenvalueDecomposition

    class EigenvalueDecomposition extends Object implements Serializable
    serialVersionUID:
      4011654467211422319L

    - #### Serialized Fields

      - ##### d

            double[] d

        Arrays for internal storage of eigenvalues.
        internal storage of eigenvalues.

      - ##### e

            double[] e

        Arrays for internal storage of eigenvalues.
        internal storage of eigenvalues.

      - ##### H

            double[][] H

        Array for internal storage of nonsymmetric Hessenberg form.
        internal storage of nonsymmetric Hessenberg form.

      - ##### issymmetric

            boolean issymmetric

        Symmetry flag.
        internal symmetry flag.

      - ##### n

            int n

        Row and column dimension (square matrix).
        matrix dimension.

      - ##### ort

            double[] ort

        Working storage for nonsymmetric algorithm.
        working storage for nonsymmetric algorithm.

      - ##### V

            double[][] V

        Array for internal storage of eigenvectors.
        internal storage of eigenvectors.

  - ### Class weka.core.matrix.ExponentialFormat

    class ExponentialFormat extends DecimalFormat implements Serializable
    serialVersionUID:
      -5298981701073897741L

    - #### Serialized Fields

      - ##### digits

            int digits

      - ##### exp

            int exp

      - ##### nf

            DecimalFormat nf

      - ##### sign

            boolean sign

      - ##### trailing

            boolean trailing

  - ### Class weka.core.matrix.FlexibleDecimalFormat

    class FlexibleDecimalFormat extends DecimalFormat implements Serializable
    serialVersionUID:
      110912192794064140L

    - #### Serialized Fields

      - ##### decimalDigits

            int decimalDigits

      - ##### digits

            int digits

      - ##### exp

            boolean exp

      - ##### expDecimalDigits

            int expDecimalDigits

      - ##### grouping

            boolean grouping

      - ##### intDigits

            int intDigits

      - ##### nf

            DecimalFormat nf

      - ##### power

            int power

      - ##### sign

            boolean sign

      - ##### trailing

            boolean trailing

  - ### Class weka.core.matrix.FloatingPointFormat

    class FloatingPointFormat extends DecimalFormat implements Serializable
    serialVersionUID:
      4500373755333429499L

    - #### Serialized Fields

      - ##### decimal

            int decimal

      - ##### nf

            DecimalFormat nf

      - ##### trailing

            boolean trailing

      - ##### width

            int width

  - ### Class weka.core.matrix.LUDecomposition

    class LUDecomposition extends Object implements Serializable
    serialVersionUID:
      -2731022568037808629L

    - #### Serialized Fields

      - ##### LU

            double[][] LU

        Array for internal storage of decomposition.
        internal array storage.

      - ##### m

            int m

        Row and column dimensions, and pivot sign.
        column dimension.

      - ##### n

            int n

        Row and column dimensions, and pivot sign.
        column dimension.

      - ##### piv

            int[] piv

        Internal storage of pivot vector.
        pivot vector.

      - ##### pivsign

            int pivsign

        Row and column dimensions, and pivot sign.
        column dimension.

  - ### Class weka.core.matrix.Matrix

    class Matrix extends Object implements Serializable
    serialVersionUID:
      7856794138418366180L

    - #### Serialized Fields

      - ##### A

            double[][] A

        Array for internal storage of elements.
        internal array storage.

      - ##### m

            int m

        Row and column dimensions.
        row dimension.

      - ##### n

            int n

        Row and column dimensions.
        row dimension.

  - ### Class weka.core.matrix.QRDecomposition

    class QRDecomposition extends Object implements Serializable
    serialVersionUID:
      -5013090736132211418L

    - #### Serialized Fields

      - ##### m

            int m

        Row and column dimensions.
        column dimension.

      - ##### n

            int n

        Row and column dimensions.
        column dimension.

      - ##### QR

            double[][] QR

        Array for internal storage of decomposition.
        internal array storage.

      - ##### Rdiag

            double[] Rdiag

        Array for internal storage of diagonal of R.
        diagonal of R.

  - ### Class weka.core.matrix.SingularValueDecomposition

    class SingularValueDecomposition extends Object implements Serializable
    serialVersionUID:
      -8738089610999867951L

    - #### Serialized Fields

      - ##### m

            int m

        Row and column dimensions.
        row dimension.

      - ##### n

            int n

        Row and column dimensions.
        row dimension.

      - ##### s

            double[] s

        Array for internal storage of singular values.
        internal storage of singular values.

      - ##### U

            double[][] U

        Arrays for internal storage of U and V.
        internal storage of U.

      - ##### V

            double[][] V

        Arrays for internal storage of U and V.
        internal storage of U.

- ## Package weka.core.neighboursearch

  - ### Class weka.core.neighboursearch.BallTree

    class BallTree extends NearestNeighbourSearch implements Serializable
    serialVersionUID:
      728763855952698328L

    - #### Serialized Fields

      - ##### m_Distances

            double[] m_Distances

        Array holding the distances of the nearest neighbours. It is filled up both by nearestNeighbour() and kNearestNeighbours().

      - ##### m_InstList

            int[] m_InstList

        The instances indices sorted inorder of appearence in the tree from left most leaf node to the right most leaf node.

      - ##### m_MaxInstancesInLeaf

            int m_MaxInstancesInLeaf

        The maximum number of instances in a leaf. A node is made into a leaf if the number of instances in it become less than or equal to this value.

      - ##### m_Root

            BallNode m_Root

        The root node of the BallTree.

      - ##### m_TreeConstructor

            BallTreeConstructor m_TreeConstructor

        The constructor method to use to build the tree.

      - ##### m_TreeStats

            TreePerformanceStats m_TreeStats

        Tree Stats variables.

  - ### Class weka.core.neighboursearch.CoverTree

    class CoverTree extends NearestNeighbourSearch implements Serializable
    serialVersionUID:
      7617412821497807586L

    - #### Serialized Fields

      - ##### il2

            double il2

        if we have base 2 then this can be viewed as 1/ln(2), which can be used later on to do il2*ln(d) instead of ln(d)/ln(2), to get log2(d), in get_scale method.

      - ##### m_Base

            double m_Base

        The base of our expansion constant. In other words the 2 in 2^i used in covering tree and separation invariants of a cover tree. P.S.: In paper it's suggested the separation invariant is relaxed in batch construction.

      - ##### m_DistanceList

            double[] m_DistanceList

        Array holding the distances of the nearest neighbours. It is filled up both by nearestNeighbour() and kNearestNeighbours().

      - ##### m_EuclideanDistance

            EuclideanDistance m_EuclideanDistance

        The euclidean distance function to use.

      - ##### m_MaxDepth

            int m_MaxDepth

        Number of nodes in the tree.

      - ##### m_NumLeaves

            int m_NumLeaves

        Number of nodes in the tree.

      - ##### m_NumNodes

            int m_NumNodes

        Number of nodes in the tree.

      - ##### m_Root

            CoverTree.CoverTreeNode m_Root

        The root node.

      - ##### m_TreeStats

            TreePerformanceStats m_TreeStats

        Tree Stats variables.

  - ### Class weka.core.neighboursearch.CoverTree.CoverTreeNode

    class CoverTreeNode extends Object implements Serializable
    serialVersionUID:
      1808760031169036512L

    - #### Serialized Fields

      - ##### children

            Stack<CoverTree.CoverTreeNode> children

        The children of the node.

      - ##### idx

            Integer idx

        Index of the instance represented by this node in the index array.

      - ##### max_dist

            double max_dist

        The distance of the furthest descendant of the node.

      - ##### num_children

            int num_children

        The number of children node has.

      - ##### parent_dist

            double parent_dist

        The distance to the nodes parent.

      - ##### scale

            int scale

        The min i that makes base^i <= max_dist.

  - ### Class weka.core.neighboursearch.FilteredNeighbourSearch

    class FilteredNeighbourSearch extends NearestNeighbourSearch implements Serializable
    serialVersionUID:
      1369174644087067375L

    - #### Serialized Fields

      - ##### m_AddID

            AddID m_AddID

        Need to use ID filter to add ID so that we can identify instances

      - ##### m_Filter

            Filter m_Filter

        The filter object to use.

      - ##### m_IndexOfID

            int m_IndexOfID

        The index of the ID attribute

      - ##### m_ModifiedSearchMethod

            NearestNeighbourSearch m_ModifiedSearchMethod

        The modified search method, where ID is skipped

      - ##### m_SearchMethod

            NearestNeighbourSearch m_SearchMethod

        The neighborhood search method to use.

  - ### Class weka.core.neighboursearch.KDTree

    class KDTree extends NearestNeighbourSearch implements Serializable
    serialVersionUID:
      1505717283763272533L

    - #### Serialized Fields

      - ##### m_DistanceList

            double[] m_DistanceList

        Array holding the distances of the nearest neighbours. It is filled up both by nearestNeighbour() and kNearestNeighbours().

      - ##### m_EuclideanDistance

            EuclideanDistance m_EuclideanDistance

        The euclidean distance function to use.

      - ##### m_InstList

            int[] m_InstList

        Indexlist of the instances of this kdtree. Instances get sorted according to the splits. the nodes of the KDTree just hold their start and end indices

      - ##### m_MaxDepth

            int m_MaxDepth

        Tree stats.

      - ##### m_MaxInstInLeaf

            int m_MaxInstInLeaf

        maximal number of instances in a leaf.

      - ##### m_MinBoxRelWidth

            double m_MinBoxRelWidth

        minimal relative width of a KDTree rectangle.

      - ##### m_NormalizeNodeWidth

            boolean m_NormalizeNodeWidth

        flag for normalizing.

      - ##### m_NumLeaves

            int m_NumLeaves

        Tree stats.

      - ##### m_NumNodes

            int m_NumNodes

        Tree stats.

      - ##### m_Root

            KDTreeNode m_Root

        The root node of the tree.

      - ##### m_Splitter

            KDTreeNodeSplitter m_Splitter

        The node splitter.

      - ##### m_TreeStats

            TreePerformanceStats m_TreeStats

        Tree Stats variables.

  - ### Class weka.core.neighboursearch.LinearNNSearch

    class LinearNNSearch extends NearestNeighbourSearch implements Serializable
    serialVersionUID:
      1915484723703917241L

    - #### Serialized Fields

      - ##### m_Distances

            double[] m_Distances

        Array holding the distances of the nearest neighbours. It is filled up both by nearestNeighbour() and kNearestNeighbours().

      - ##### m_SkipIdentical

            boolean m_SkipIdentical

        Whether to skip instances from the neighbours that are identical to the query instance.

  - ### Class weka.core.neighboursearch.NearestNeighbourSearch

    class NearestNeighbourSearch extends Object implements Serializable
    serialVersionUID:
      7516898393890379876L

    - #### Serialized Fields

      - ##### m_DistanceFunction

            DistanceFunction m_DistanceFunction

        the distance function used.

      - ##### m_Instances

            Instances m_Instances

        The neighbourhood of instances to find neighbours in.

      - ##### m_kNN

            int m_kNN

        The number of neighbours to find.

      - ##### m_MeasurePerformance

            boolean m_MeasurePerformance

        Should we measure Performance.

      - ##### m_Stats

            PerformanceStats m_Stats

        Performance statistics.

  - ### Class weka.core.neighboursearch.PerformanceStats

    class PerformanceStats extends Object implements Serializable
    serialVersionUID:
      -7215110351388368092L

    - #### Serialized Fields

      - ##### m_CoordCount

            double m_CoordCount

        The number of coordinates looked at for the current/last query.

      - ##### m_MaxC

            double m_MaxC

        The min and max coordinates(attributes) looked at per query.

      - ##### m_MaxP

            double m_MaxP

        The min and max data points looked for a query by the NNS algorithm.

      - ##### m_MinC

            double m_MinC

        The min and max coordinates(attributes) looked at per query.

      - ##### m_MinP

            double m_MinP

        The min and max data points looked for a query by the NNS algorithm.

      - ##### m_NumQueries

            int m_NumQueries

        The total number of queries looked at.

      - ##### m_PointCount

            double m_PointCount

        The number of data points looked at for the current/last query.

      - ##### m_SumC

            double m_SumC

        The sum of coordinates/attributes looked at for all the queries.

      - ##### m_SumP

            double m_SumP

        The sum of data points looked at for all the queries.

      - ##### m_SumSqC

            double m_SumSqC

        The squared sum of coordinates/attributes looked at for all the queries.

      - ##### m_SumSqP

            double m_SumSqP

        The squared sum of data points looked at for all the queries.

  - ### Class weka.core.neighboursearch.TreePerformanceStats

    class TreePerformanceStats extends PerformanceStats implements Serializable
    serialVersionUID:
      -6637636693340810373L

    - #### Serialized Fields

      - ##### m_IntNodeCount

            int m_IntNodeCount

        The number of internal nodes looked at for the current/last query.

      - ##### m_LeafCount

            int m_LeafCount

        The number of leaf nodes looked at for the current/last query.

      - ##### m_MaxIntNodes

            int m_MaxIntNodes

        The min and max number internal nodes looked for a query by the tree based NNS algorithm.

      - ##### m_MaxLeaves

            int m_MaxLeaves

        The min and max number leaf nodes looked for a query by the tree based NNS algorithm.

      - ##### m_MinIntNodes

            int m_MinIntNodes

        The min and max number internal nodes looked for a query by the tree based NNS algorithm.

      - ##### m_MinLeaves

            int m_MinLeaves

        The min and max number leaf nodes looked for a query by the tree based NNS algorithm.

      - ##### m_SumIntNodes

            int m_SumIntNodes

        The sum of internal nodes looked at for all the queries.

      - ##### m_SumLeaves

            int m_SumLeaves

        The sum of leaf nodes looked at for all the queries.

      - ##### m_SumSqIntNodes

            int m_SumSqIntNodes

        The squared sum of internal nodes looked at for all the queries.

      - ##### m_SumSqLeaves

            int m_SumSqLeaves

        The squared sum of leaf nodes looked at for all the queries.

- ## Package weka.core.neighboursearch.balltrees

  - ### Class weka.core.neighboursearch.balltrees.BallNode

    class BallNode extends Object implements Serializable
    serialVersionUID:
      -8289151861759883510L

    - #### Serialized Fields

      - ##### m_End

            int m_End

        The end index of the portion of the master index array, which stores indices of the instances/points the node contains.

      - ##### m_Left

            BallNode m_Left

        The left child of the node.

      - ##### m_NodeNumber

            int m_NodeNumber

        The node number/id.

      - ##### m_NumInstances

            int m_NumInstances

        The number of instances/points in the node.

      - ##### m_Pivot

            Instance m_Pivot

        The pivot/centre of the ball.

      - ##### m_Radius

            double m_Radius

        The radius of this ball (hyper sphere).

      - ##### m_Right

            BallNode m_Right

        The right child of the node.

      - ##### m_SplitAttrib

            int m_SplitAttrib

        The attribute that splits this node (not always used).

      - ##### m_SplitVal

            double m_SplitVal

        The value of m_SpiltAttrib that splits this node (not always used).

      - ##### m_Start

            int m_Start

        The start index of the portion of the master index array, which stores the indices of the instances/points the node contains.

  - ### Class weka.core.neighboursearch.balltrees.BallSplitter

    class BallSplitter extends Object implements Serializable
    serialVersionUID:
      -2233739562654159948L

    - #### Serialized Fields

      - ##### m_DistanceFunction

            EuclideanDistance m_DistanceFunction

        The distance function (metric) from which the tree is (OR is to be) built.

      - ##### m_Instances

            Instances m_Instances

        The instance on which the tree is built.

      - ##### m_Instlist

            int[] m_Instlist

        The master index array that'll be reshuffled as nodes are split (and the tree is constructed).

  - ### Class weka.core.neighboursearch.balltrees.BallTreeConstructor

    class BallTreeConstructor extends Object implements Serializable
    serialVersionUID:
      982315539809240771L

    - #### Serialized Fields

      - ##### m_DistanceFunction

            DistanceFunction m_DistanceFunction

        The distance function to use to build the tree.

      - ##### m_FullyContainChildBalls

            boolean m_FullyContainChildBalls

        Should a parent ball completely enclose the balls of its two children, or only the points inside its children.

      - ##### m_Instances

            Instances m_Instances

        The instances on which to build the tree.

      - ##### m_InstList

            int[] m_InstList

        The master index array.

      - ##### m_MaxDepth

            int m_MaxDepth

        The depth of the built tree.

      - ##### m_MaxInstancesInLeaf

            int m_MaxInstancesInLeaf

        The maximum number of instances allowed in a leaf.

      - ##### m_MaxRelLeafRadius

            double m_MaxRelLeafRadius

        The maximum relative radius of a leaf node (relative to the smallest ball enclosing all the data (training) points).

      - ##### m_NumLeaves

            int m_NumLeaves

        The number of leaf nodes in the built tree.

      - ##### m_NumNodes

            int m_NumNodes

        The number of internal and leaf nodes in the built tree.

  - ### Class weka.core.neighboursearch.balltrees.BottomUpConstructor

    class BottomUpConstructor extends BallTreeConstructor implements Serializable
    serialVersionUID:
      5864250777657707687L

  - ### Class weka.core.neighboursearch.balltrees.MedianDistanceFromArbitraryPoint

    class MedianDistanceFromArbitraryPoint extends BallSplitter implements Serializable
    serialVersionUID:
      5617378551363700558L

    - #### Serialized Fields

      - ##### m_Rand

            Random m_Rand

        Random number generator for selecting an abitrary (random) point.

      - ##### m_RandSeed

            int m_RandSeed

        Seed for random number generator.

  - ### Class weka.core.neighboursearch.balltrees.MedianOfWidestDimension

    class MedianOfWidestDimension extends BallSplitter implements Serializable
    serialVersionUID:
      3054842574468790421L

    - #### Serialized Fields

      - ##### m_NormalizeDimWidths

            boolean m_NormalizeDimWidths

        Should we normalize the widths(ranges) of the dimensions (attributes) before selecting the widest one.

  - ### Class weka.core.neighboursearch.balltrees.MiddleOutConstructor

    class MiddleOutConstructor extends BallTreeConstructor implements Serializable
    serialVersionUID:
      -8523314263062524462L

    - #### Serialized Fields

      - ##### m_RandomInitialAnchor

            boolean m_RandomInitialAnchor

        True if the initial anchor is chosen randomly. False if it is the furthest point from the mean/centroid.

      - ##### m_RSeed

            int m_RSeed

        Seed form random number generator.

      - ##### rand

            Random rand

        The random number generator for selecting the first anchor point randomly (if selecting randomly).

      - ##### rootRadius

            double rootRadius

        The radius of the smallest ball enclosing all the data points.

  - ### Class weka.core.neighboursearch.balltrees.MiddleOutConstructor.ListNode

    class ListNode extends Object implements Serializable

    - #### Serialized Fields

      - ##### distance

            double distance

        The distance of the point to the anchor.

      - ##### idx

            int idx

        The index of the point.

  - ### Class weka.core.neighboursearch.balltrees.MiddleOutConstructor.MyIdxList

    class MyIdxList extends Object implements Serializable
    serialVersionUID:
      -2283869109722934927L

    - #### Serialized Fields

      - ##### m_List

            ArrayList<weka.core.neighboursearch.balltrees.MiddleOutConstructor.ListNode> m_List

        The array list backing this list

  - ### Class weka.core.neighboursearch.balltrees.PointsClosestToFurthestChildren

    class PointsClosestToFurthestChildren extends BallSplitter implements Serializable
    serialVersionUID:
      -2947177543565818260L

  - ### Class weka.core.neighboursearch.balltrees.TopDownConstructor

    class TopDownConstructor extends BallTreeConstructor implements Serializable
    serialVersionUID:
      -5150140645091889979L

    - #### Serialized Fields

      - ##### m_Splitter

            BallSplitter m_Splitter

        The BallSplitter algorithm used by the TopDown BallTree constructor, if it is selected.

- ## Package weka.core.neighboursearch.covertrees

  - ### Class weka.core.neighboursearch.covertrees.Stack

    class Stack extends Object implements Serializable
    serialVersionUID:
      5604056321825539264L

    - #### Serialized Fields

      - ##### elements

            ArrayList<T> elements

        The elements inside the stack.

      - ##### length

            int length

        The number of elements in the stack.

- ## Package weka.core.neighboursearch.kdtrees

  - ### Class weka.core.neighboursearch.kdtrees.KDTreeNode

    class KDTreeNode extends Object implements Serializable
    serialVersionUID:
      -3660396067582792648L

    - #### Serialized Fields

      - ##### m_End

            int m_End

        The end index of the portion of the master index array, which stores indices of the instances/points the node contains.

      - ##### m_Left

            KDTreeNode m_Left

        left subtree; contains instances with smaller or equal to split value.

      - ##### m_NodeNumber

            int m_NodeNumber

        node number (only for debug).

      - ##### m_NodeRanges

            double[][] m_NodeRanges

        lowest and highest value and width (= high - low) for each dimension.

      - ##### m_NodesRectBounds

            double[][] m_NodesRectBounds

        The lo and high bounds of the hyper rectangle described by the node.

      - ##### m_Right

            KDTreeNode m_Right

        right subtree; contains instances with larger than split value.

      - ##### m_SplitDim

            int m_SplitDim

        attribute to split on.

      - ##### m_SplitValue

            double m_SplitValue

        value to split on.

      - ##### m_Start

            int m_Start

        The start index of the portion of the master index array, which stores the indices of the instances/points the node contains.

  - ### Class weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter

    class KDTreeNodeSplitter extends Object implements Serializable
    serialVersionUID:
      7222420817095067166L

    - #### Serialized Fields

      - ##### m_EuclideanDistance

            EuclideanDistance m_EuclideanDistance

        The distance function used for building the tree.

      - ##### m_Instances

            Instances m_Instances

        The instances that'll be used for tree construction.

      - ##### m_InstList

            int[] m_InstList

        The master index array that'll be reshuffled as nodes are split and the tree is constructed.

      - ##### m_NormalizeNodeWidth

            boolean m_NormalizeNodeWidth

        Stores whether if the width of a KDTree node is normalized or not.

  - ### Class weka.core.neighboursearch.kdtrees.KMeansInpiredMethod

    class KMeansInpiredMethod extends KDTreeNodeSplitter implements Serializable
    serialVersionUID:
      -866783749124714304L

  - ### Class weka.core.neighboursearch.kdtrees.MedianOfWidestDimension

    class MedianOfWidestDimension extends KDTreeNodeSplitter implements Serializable
    serialVersionUID:
      1383443320160540663L

  - ### Class weka.core.neighboursearch.kdtrees.MidPointOfWidestDimension

    class MidPointOfWidestDimension extends KDTreeNodeSplitter implements Serializable
    serialVersionUID:
      -7617277960046591906L

  - ### Class weka.core.neighboursearch.kdtrees.SlidingMidPointOfWidestSide

    class SlidingMidPointOfWidestSide extends KDTreeNodeSplitter implements Serializable
    serialVersionUID:
      852857628205680562L

- ## Package weka.core.packageManagement

  - ### Class weka.core.packageManagement.DefaultPackage

    class DefaultPackage extends Package implements Serializable
    serialVersionUID:
      3643121886457892125L

    - #### Serialized Fields

      - ##### m_packageHome

            File m_packageHome

        Holds the home directory for installed packages

  - ### Class weka.core.packageManagement.DefaultPackageManager.DefaultPMDefaults

    class DefaultPMDefaults extends Defaults implements Serializable
    serialVersionUID:
      -1428588514991146709L

  - ### Class weka.core.packageManagement.Package

    class Package extends Object implements Serializable
    serialVersionUID:
      -8193697646938632764L

    - #### Serialized Fields

      - ##### m_packageMetaData

            Map<?,?> m_packageMetaData

        The meta data for the package

- ## Package weka.core.pmml

  - ### Class weka.core.pmml.Array

    class Array extends Object implements Serializable
    serialVersionUID:
      4286234448957826177L

    - #### Serialized Fields

      - ##### m_type

            Array.ArrayType m_type

        The type of the array

      - ##### m_values

            ArrayList<String> m_values

        The values of the array

  - ### Class weka.core.pmml.BuiltInArithmetic

    class BuiltInArithmetic extends Function implements Serializable
    serialVersionUID:
      2275009453597279459L

    - #### Serialized Fields

      - ##### m_operator

            weka.core.pmml.BuiltInArithmetic.Operator m_operator

        The operator for this function

  - ### Class weka.core.pmml.BuiltInMath

    class BuiltInMath extends Function implements Serializable
    serialVersionUID:
      -8092338695602573652L

    - #### Serialized Fields

      - ##### m_func

            weka.core.pmml.BuiltInMath.MathFunc m_func

        The function to apply

  - ### Class weka.core.pmml.BuiltInString

    class BuiltInString extends Function implements Serializable
    serialVersionUID:
      -7391516909331728653L

    - #### Serialized Fields

      - ##### m_func

            weka.core.pmml.BuiltInString.StringFunc m_func

        The function to apply

      - ##### m_outputDef

            Attribute m_outputDef

        The output structure produced by this function

  - ### Class weka.core.pmml.Constant

    class Constant extends Expression implements Serializable
    serialVersionUID:
      -304829687822452424L

    - #### Serialized Fields

      - ##### m_categoricalConst

            String m_categoricalConst

      - ##### m_continuousConst

            double m_continuousConst

  - ### Class weka.core.pmml.DefineFunction

    class DefineFunction extends Function implements Serializable
    serialVersionUID:
      -1976646917527243888L

    - #### Serialized Fields

      - ##### m_expression

            Expression m_expression

        The Expression for this function to use

      - ##### m_optype

            FieldMetaInfo.Optype m_optype

        The optype for this function

      - ##### m_parameters

            ArrayList<weka.core.pmml.DefineFunction.ParameterField> m_parameters

        The list of parameters expected by this function. We can use this to do some error/type checking when users call setParameterDefs() on us

  - ### Class weka.core.pmml.DefineFunction.ParameterField

    class ParameterField extends FieldMetaInfo implements Serializable
    serialVersionUID:
      3918895902507585558L

  - ### Class weka.core.pmml.DerivedFieldMetaInfo

    class DerivedFieldMetaInfo extends FieldMetaInfo implements Serializable
    serialVersionUID:
      875736989396755241L

    - #### Serialized Fields

      - ##### m_displayName

            String m_displayName

        display name

      - ##### m_expression

            Expression m_expression

        the single expression that defines the value of this field

      - ##### m_values

            ArrayList<FieldMetaInfo.Value> m_values

        the list of values (if the field is ordinal) - may be of size zero if none are specified. If none are specified, we may be able to construct this by querying the Expression in this derived field

  - ### Class weka.core.pmml.Discretize

    class Discretize extends Expression implements Serializable
    serialVersionUID:
      -5809107997906180082L

    - #### Serialized Fields

      - ##### m_bins

            ArrayList<weka.core.pmml.Discretize.DiscretizeBin> m_bins

        The bins for this discretization

      - ##### m_defaultValue

            String m_defaultValue

        The default value (if defined)

      - ##### m_defaultValueDefined

            boolean m_defaultValueDefined

        True if a default value has been specified

      - ##### m_fieldIndex

            int m_fieldIndex

        The index of the field

      - ##### m_fieldName

            String m_fieldName

        The name of the field to be discretized

      - ##### m_mapMissingDefined

            boolean m_mapMissingDefined

        True if a replacement for missing values has been specified

      - ##### m_mapMissingTo

            String m_mapMissingTo

        The value of the missing value replacement (if defined)

      - ##### m_outputDef

            Attribute m_outputDef

        The output structure of this discretization

  - ### Class weka.core.pmml.Discretize.DiscretizeBin

    class DiscretizeBin extends Object implements Serializable
    serialVersionUID:
      5810063243316808400L

    - #### Serialized Fields

      - ##### m_binValue

            String m_binValue

        The bin value for this DiscretizeBin

      - ##### m_intervals

            ArrayList<FieldMetaInfo.Interval> m_intervals

        The intervals for this DiscretizeBin

      - ##### m_numericBinValue

            double m_numericBinValue

        If the optype is continuous or ordinal, we will attempt to parse the bin value as a number and store it here.

  - ### Class weka.core.pmml.Expression

    class Expression extends Object implements Serializable
    serialVersionUID:
      4448840549804800321L

    - #### Serialized Fields

      - ##### m_fieldDefs

            ArrayList<Attribute> m_fieldDefs

        The field defs

      - ##### m_opType

            FieldMetaInfo.Optype m_opType

        The optype of this Expression

  - ### Class weka.core.pmml.FieldMetaInfo

    class FieldMetaInfo extends Object implements Serializable
    serialVersionUID:
      -6116715567129830143L

    - #### Serialized Fields

      - ##### m_fieldName

            String m_fieldName

        the name of the field

      - ##### m_optype

            FieldMetaInfo.Optype m_optype

        The optype for the target

  - ### Class weka.core.pmml.FieldMetaInfo.Interval

    class Interval extends Object implements Serializable
    serialVersionUID:
      -7339790632684638012L

    - #### Serialized Fields

      - ##### m_closure

            FieldMetaInfo.Interval.Closure m_closure

      - ##### m_leftMargin

            double m_leftMargin

        The left boundary value

      - ##### m_rightMargin

            double m_rightMargin

        The right boundary value

  - ### Class weka.core.pmml.FieldMetaInfo.Value

    class Value extends Object implements Serializable
    serialVersionUID:
      -3981030320273649739L

    - #### Serialized Fields

      - ##### m_displayValue

            String m_displayValue

        The display value (might hold a human readable value - e.g. product name instead of cryptic code).

      - ##### m_property

            FieldMetaInfo.Value.Property m_property

      - ##### m_value

            String m_value

        The value

  - ### Class weka.core.pmml.FieldRef

    class FieldRef extends Expression implements Serializable
    serialVersionUID:
      -8009605897876168409L

    - #### Serialized Fields

      - ##### m_fieldName

            String m_fieldName

        The name of the field to reference

  - ### Class weka.core.pmml.Function

    class Function extends Object implements Serializable
    serialVersionUID:
      -6997738288201933171L

    - #### Serialized Fields

      - ##### m_functionName

            String m_functionName

        The name of this function

      - ##### m_parameterDefs

            ArrayList<Attribute> m_parameterDefs

        The structure of the parameters to this function

  - ### Class weka.core.pmml.MappingInfo

    class MappingInfo extends Object implements Serializable
    serialVersionUID:
      -475467721189397466L

    - #### Serialized Fields

      - ##### m_fieldsMap

            int[] m_fieldsMap

        Map the incoming attributes to the mining schema attributes. Each entry holds the index of the incoming attribute that corresponds to this mining schema attribute.

      - ##### m_fieldsMappingText

            String m_fieldsMappingText

        Holds a textual description of the fields mapping

      - ##### m_log

            Logger m_log

        For logging

      - ##### m_nominalValueMaps

            int[][] m_nominalValueMaps

        Map indexes for nominal values in incoming structure to those in the mining schema. There will be as many entries as there are attributes in this array. Non-nominal attributes will have null entries. Each non-null entry is an array of integer indexes. Each entry in a given array (for a given attribute) holds the index of the mining schema value that corresponds to this incoming value. UNKNOWN_NOMINAL_VALUE is used as the index for those incoming values that are not defined in the mining schema.

  - ### Class weka.core.pmml.MiningFieldMetaInfo

    class MiningFieldMetaInfo extends FieldMetaInfo implements Serializable
    serialVersionUID:
      -1256774332779563185L

    - #### Serialized Fields

      - ##### m_highValue

            double m_highValue

        outlier high value

      - ##### m_importance

            double m_importance

        importance (if defined)

      - ##### m_index

            int m_index

        the index of the field in the mining schema Instances

      - ##### m_lowValue

            double m_lowValue

        outlier low value

      - ##### m_miningSchemaI

            Instances m_miningSchemaI

        mining schema (needed for toString method)

      - ##### m_missingValueReplacementNominal

            String m_missingValueReplacementNominal

        actual missing value replacements (if specified)

      - ##### m_missingValueReplacementNumeric

            double m_missingValueReplacementNumeric

      - ##### m_missingValueTreatmentMethod

            weka.core.pmml.MiningFieldMetaInfo.Missing m_missingValueTreatmentMethod

        missing values treatment method

      - ##### m_optypeOverride

            FieldMetaInfo.Optype m_optypeOverride

        optype overrides (override data dictionary type - NOT SUPPORTED AT PRESENT)

      - ##### m_outlierTreatmentMethod

            weka.core.pmml.MiningFieldMetaInfo.Outlier m_outlierTreatmentMethod

        outlier treatmemnt method

      - ##### m_usageType

            weka.core.pmml.MiningFieldMetaInfo.Usage m_usageType

        usage type

  - ### Class weka.core.pmml.MiningSchema

    class MiningSchema extends Object implements Serializable
    serialVersionUID:
      7144380586726330455L

    - #### Serialized Fields

      - ##### m_derivedMeta

            ArrayList<DerivedFieldMetaInfo> m_derivedMeta

        Meta information about derived fields (those defined in the TransformationDictionary followed by those defined in LocalTransformations)

      - ##### m_fieldInstancesStructure

            Instances m_fieldInstancesStructure

        The structure of all the fields (both mining schema and derived) as Instances

      - ##### m_miningMeta

            ArrayList<MiningFieldMetaInfo> m_miningMeta

        Meta information about the mining schema fields

      - ##### m_miningSchemaInstancesStructure

            Instances m_miningSchemaInstancesStructure

        Just the mining schema fields as Instances

      - ##### m_targetMetaInfo

            TargetMetaInfo m_targetMetaInfo

        target meta info (may be null if not defined)

      - ##### m_transformationDictionary

            weka.core.pmml.TransformationDictionary m_transformationDictionary

        The transformation dictionary (if defined)

  - ### Class weka.core.pmml.NormContinuous

    class NormContinuous extends Expression implements Serializable
    serialVersionUID:
      4714332374909851542L

    - #### Serialized Fields

      - ##### m_fieldIndex

            int m_fieldIndex

        The index of the field

      - ##### m_fieldName

            String m_fieldName

        The name of the field to use

      - ##### m_linearNormNorm

            double[] m_linearNormNorm

        norm values for the LinearNorm entries

      - ##### m_linearNormOrig

            double[] m_linearNormOrig

        original values for the LinearNorm entries

      - ##### m_mapMissingDefined

            boolean m_mapMissingDefined

        True if a replacement for missing values has been specified

      - ##### m_mapMissingTo

            double m_mapMissingTo

        The value of the missing value replacement (if defined)

      - ##### m_outlierTreatmentMethod

            weka.core.pmml.MiningFieldMetaInfo.Outlier m_outlierTreatmentMethod

        Outlier treatment method (default = asIs)

  - ### Class weka.core.pmml.NormDiscrete

    class NormDiscrete extends Expression implements Serializable
    serialVersionUID:
      -8854409417983908220L

    - #### Serialized Fields

      - ##### m_field

            Attribute m_field

        The actual attribute itself

      - ##### m_fieldIndex

            int m_fieldIndex

        The index of the attribute

      - ##### m_fieldName

            String m_fieldName

        The name of the field to lookup our value in

      - ##### m_fieldValue

            String m_fieldValue

        The actual value (as a String) that will correspond to an output of 1

      - ##### m_fieldValueIndex

            int m_fieldValueIndex

        If we are referring to a nominal (rather than String) attribute then this holds the index of the value in question. Will be faster than searching for the value each time.

      - ##### m_mapMissingDefined

            boolean m_mapMissingDefined

        True if a replacement for missing values has been specified

      - ##### m_mapMissingTo

            double m_mapMissingTo

        The value of the missing value replacement (if defined)

  - ### Class weka.core.pmml.SparseArray

    class SparseArray extends Array implements Serializable
    serialVersionUID:
      8129550573612673674L

    - #### Serialized Fields

      - ##### m_indices

            List<Integer> m_indices

        The indices of the sparse array

      - ##### m_numNonZero

            int m_numNonZero

        The number of non-zero elements

      - ##### m_numValues

            int m_numValues

        The size of the array if known

  - ### Class weka.core.pmml.TargetMetaInfo

    class TargetMetaInfo extends FieldMetaInfo implements Serializable
    serialVersionUID:
      863500462237904927L

    - #### Serialized Fields

      - ##### m_castInteger

            String m_castInteger

        cast integers (default no casting)

      - ##### m_defaultValueOrPriorProbs

            double[] m_defaultValueOrPriorProbs

        default value (numeric) or prior distribution (categorical)

      - ##### m_displayValues

            ArrayList<String> m_displayValues

        corresponding display values

      - ##### m_max

            double m_max

      - ##### m_min

            double m_min

        min and max

      - ##### m_rescaleConstant

            double m_rescaleConstant

        re-scaling of target value (if defined)

      - ##### m_rescaleFactor

            double m_rescaleFactor

      - ##### m_values

            ArrayList<String> m_values

        for categorical values. Actual values

  - ### Class weka.core.pmml.VectorDictionary

    class VectorDictionary extends Object implements Serializable
    serialVersionUID:
      -5538024467333813123L

    - #### Serialized Fields

      - ##### m_numberOfVectors

            int m_numberOfVectors

        The number of support vectors in the dictionary

      - ##### m_vectorFields

            List<FieldRef> m_vectorFields

        The fields accessed by the support vectors

      - ##### m_vectorInstances

            Map<String,VectorInstance> m_vectorInstances

        The vectors in the dictionary

  - ### Class weka.core.pmml.VectorInstance

    class VectorInstance extends Object implements Serializable
    serialVersionUID:
      -7543200367512646290L

    - #### Serialized Fields

      - ##### m_ID

            String m_ID

        The ID of this instance

      - ##### m_values

            Array m_values

        The usually sparse elements of this vector

      - ##### m_vectorFields

            List<FieldRef> m_vectorFields

        The fields indexed by this VectorInstance

- ## Package weka.core.scripting

  - ### Class weka.core.scripting.Groovy

    class Groovy extends Object implements Serializable
    serialVersionUID:
      -2628766602043134673L

    - #### Serialized Fields

      - ##### m_ClassLoader

            Object m_ClassLoader

        the classloader.

  - ### Class weka.core.scripting.Jython

    class Jython extends Object implements Serializable
    serialVersionUID:
      -6972298704460209252L

    - #### Serialized Fields

      - ##### m_Interpreter

            Object m_Interpreter

        the interpreter

- ## Package weka.core.stemmers

  - ### Class weka.core.stemmers.IteratedLovinsStemmer

    class IteratedLovinsStemmer extends LovinsStemmer implements Serializable
    serialVersionUID:
      960689687163788264L

  - ### Class weka.core.stemmers.LovinsStemmer

    class LovinsStemmer extends Object implements Serializable
    serialVersionUID:
      -6113024782588197L

  - ### Class weka.core.stemmers.NullStemmer

    class NullStemmer extends Object implements Serializable
    serialVersionUID:
      -3671261636532625496L

  - ### Class weka.core.stemmers.SnowballStemmer

    class SnowballStemmer extends Object implements Serializable
    serialVersionUID:
      -6111170431963015178L

    - #### Serialized Fields

      - ##### m_Stemmer

            Object m_Stemmer

        the current stemmer.

- ## Package weka.core.stopwords

  - ### Class weka.core.stopwords.AbstractFileBasedStopwords

    class AbstractFileBasedStopwords extends AbstractStopwords implements Serializable
    serialVersionUID:
      -8568762652879773063L

    - #### Serialized Fields

      - ##### m_Stopwords

            File m_Stopwords

        a file containing stopwords.

  - ### Class weka.core.stopwords.AbstractStopwords

    class AbstractStopwords extends Object implements Serializable
    serialVersionUID:
      -1975256329586388142L

    - #### Serialized Fields

      - ##### m_Debug

            boolean m_Debug

        debugging flag.

      - ##### m_Initialized

            boolean m_Initialized

        whether the scheme has been initialized.

  - ### Class weka.core.stopwords.MultiStopwords

    class MultiStopwords extends AbstractStopwords implements Serializable
    serialVersionUID:
      -8568762652879773063L

    - #### Serialized Fields

      - ##### m_Stopwords

            StopwordsHandler[] m_Stopwords

        the stopwords algorithms to use.

  - ### Class weka.core.stopwords.Null

    class Null extends AbstractStopwords implements Serializable
    serialVersionUID:
      -3319681866579617385L

  - ### Class weka.core.stopwords.Rainbow

    class Rainbow extends AbstractStopwords implements Serializable
    serialVersionUID:
      -722795295494945193L

    - #### Serialized Fields

      - ##### m_Words

            HashSet<String> m_Words

        The hash set containing the list of stopwords.

  - ### Class weka.core.stopwords.RegExpFromFile

    class RegExpFromFile extends AbstractFileBasedStopwords implements Serializable
    serialVersionUID:
      -722795295494945193L

    - #### Serialized Fields

      - ##### m_Patterns

            List<Pattern> m_Patterns

        The list of regular expressions.

  - ### Class weka.core.stopwords.WordsFromFile

    class WordsFromFile extends AbstractFileBasedStopwords implements Serializable
    serialVersionUID:
      -722795295494945193L

    - #### Serialized Fields

      - ##### m_Words

            HashSet<String> m_Words

        The hash set containing the list of stopwords.

- ## Package weka.core.tokenizers

  - ### Class weka.core.tokenizers.AlphabeticTokenizer

    class AlphabeticTokenizer extends Tokenizer implements Serializable
    serialVersionUID:
      6705199562609861697L

    - #### Serialized Fields

      - ##### m_CurrentPos

            int m_CurrentPos

        the current position

      - ##### m_Str

            char[] m_Str

        the characters of the string

  - ### Class weka.core.tokenizers.CharacterDelimitedTokenizer

    class CharacterDelimitedTokenizer extends Tokenizer implements Serializable
    serialVersionUID:
      -3091468793633408477L

    - #### Serialized Fields

      - ##### m_Delimiters

            String m_Delimiters

        Delimiters used in tokenization

  - ### Class weka.core.tokenizers.CharacterNGramTokenizer

    class CharacterNGramTokenizer extends Tokenizer implements Serializable
    serialVersionUID:
      -1181896253171647218L

    - #### Serialized Fields

      - ##### m_CurrentPosition

            int m_CurrentPosition

        the current position for returning elements

      - ##### m_N

            int m_N

        the current length of the N-grams

      - ##### m_NMax

            int m_NMax

        the maximum number of N

      - ##### m_NMin

            int m_NMin

        the minimum number of N

      - ##### m_String

            String m_String

        the string to tokenize

  - ### Class weka.core.tokenizers.NGramTokenizer

    class NGramTokenizer extends CharacterDelimitedTokenizer implements Serializable
    serialVersionUID:
      -2181896254171647219L

    - #### Serialized Fields

      - ##### m_CurrentPosition

            int m_CurrentPosition

        the current position for returning elements

      - ##### m_MaxPosition

            int m_MaxPosition

        the number of strings available

      - ##### m_N

            int m_N

        the current length of the N-grams

      - ##### m_NMax

            int m_NMax

        the maximum number of N

      - ##### m_NMin

            int m_NMin

        the minimum number of N

      - ##### m_SplitString

            String[] m_SplitString

        all the available grams

  - ### Class weka.core.tokenizers.Tokenizer

    class Tokenizer extends Object implements Serializable
    serialVersionUID:
      7781271062738973996L

  - ### Class weka.core.tokenizers.WordTokenizer

    class WordTokenizer extends CharacterDelimitedTokenizer implements Serializable
    serialVersionUID:
      -930893034037880773L

- ## Package weka.core.xml

  - ### Class weka.core.xml.XMLInstances

    class XMLInstances extends XMLDocument implements Serializable
    serialVersionUID:
      3626821327547416099L

    - #### Serialized Fields

      - ##### m_Instances

            Instances m_Instances

        the underlying Instances

      - ##### m_Precision

            int m_Precision

        the precision for numbers

- ## Package weka.datagenerators

  - ### Class weka.datagenerators.ClassificationGenerator

    class ClassificationGenerator extends DataGenerator implements Serializable
    serialVersionUID:
      -5261662546673517844L

    - #### Serialized Fields

      - ##### m_NumExamples

            int m_NumExamples

        Number of instances

  - ### Class weka.datagenerators.ClusterDefinition

    class ClusterDefinition extends Object implements Serializable
    serialVersionUID:
      -5950001207047429961L

    - #### Serialized Fields

      - ##### m_Parent

            ClusterGenerator m_Parent

        the parent of the cluster

  - ### Class weka.datagenerators.ClusterGenerator

    class ClusterGenerator extends DataGenerator implements Serializable
    serialVersionUID:
      6131722618472046365L

    - #### Serialized Fields

      - ##### m_ClassFlag

            boolean m_ClassFlag

        class flag

      - ##### m_NumAttributes

            int m_NumAttributes

        Number of attribute the dataset should have

  - ### Class weka.datagenerators.DataGenerator

    class DataGenerator extends Object implements Serializable
    serialVersionUID:
      -3698585946221802578L

    - #### Serialized Fields

      - ##### m_CreatingRelationName

            boolean m_CreatingRelationName

        This flag is no longer used (left here to maintain compatibility for serialization)

      - ##### m_DatasetFormat

            Instances m_DatasetFormat

        The format for the generated dataset

      - ##### m_Debug

            boolean m_Debug

        Debugging mode

      - ##### m_NumExamplesAct

            int m_NumExamplesAct

        Number of instances that should be produced into the dataset this number is by default m_NumExamples, but can be reset by the generator

      - ##### m_Random

            Random m_Random

        random number generator

      - ##### m_RelationName

            String m_RelationName

        Relation name specified by the user (relation name will be auto-generated if empty)

      - ##### m_Seed

            int m_Seed

        random number generator seed

  - ### Class weka.datagenerators.RegressionGenerator

    class RegressionGenerator extends DataGenerator implements Serializable
    serialVersionUID:
      3073254041275658221L

    - #### Serialized Fields

      - ##### m_NumExamples

            int m_NumExamples

        Number of instances

  - ### Class weka.datagenerators.Test

    class Test extends Object implements Serializable
    serialVersionUID:
      -8890645875887157782L

    - #### Serialized Fields

      - ##### m_AttIndex

            int m_AttIndex

        the attribute index

      - ##### m_Dataset

            Instances m_Dataset

        the dataset

      - ##### m_Not

            boolean m_Not

        whether to negate the test

      - ##### m_Split

            double m_Split

        the split

- ## Package weka.datagenerators.classifiers.classification

  - ### Class weka.datagenerators.classifiers.classification.Agrawal

    class Agrawal extends ClassificationGenerator implements Serializable
    serialVersionUID:
      2254651939636143025L

    - #### Serialized Fields

      - ##### m_BalanceClass

            boolean m_BalanceClass

        whether to balance the class

      - ##### m_Function

            int m_Function

        the function to use for generating the data

      - ##### m_lastLabel

            double m_lastLabel

        the last class label that was generated

      - ##### m_nextClassShouldBeZero

            boolean m_nextClassShouldBeZero

        used for balancing the class

      - ##### m_PerturbationFraction

            double m_PerturbationFraction

        the perturabation fraction

  - ### Class weka.datagenerators.classifiers.classification.BayesNet

    class BayesNet extends ClassificationGenerator implements Serializable
    serialVersionUID:
      -796118162379901512L

    - #### Serialized Fields

      - ##### m_Generator

            BayesNetGenerator m_Generator

        the bayesian net generator, that produces the actual data

  - ### Class weka.datagenerators.classifiers.classification.LED24

    class LED24 extends ClassificationGenerator implements Serializable
    serialVersionUID:
      -7880209100415868737L

    - #### Serialized Fields

      - ##### m_NoisePercent

            double m_NoisePercent

        the noise rate

      - ##### m_numIrrelevantAttributes

            int m_numIrrelevantAttributes

        used for generating the output, i.e., the additional noise attributes

  - ### Class weka.datagenerators.classifiers.classification.RandomRBF

    class RandomRBF extends ClassificationGenerator implements Serializable
    serialVersionUID:
      6069033710635728720L

    - #### Serialized Fields

      - ##### m_centroidClasses

            int[] m_centroidClasses

        the classes of the centroids

      - ##### m_centroids

            double[][] m_centroids

        the centroids

      - ##### m_centroidStdDevs

            double[] m_centroidStdDevs

        the stddevs of the centroids

      - ##### m_centroidWeights

            double[] m_centroidWeights

        the weights of the centroids

      - ##### m_NumAttributes

            int m_NumAttributes

        Number of attribute the dataset should have

      - ##### m_NumCentroids

            int m_NumCentroids

        the number of centroids to use for generation

      - ##### m_NumClasses

            int m_NumClasses

        Number of Classes the dataset should have

  - ### Class weka.datagenerators.classifiers.classification.RDG1

    class RDG1 extends ClassificationGenerator implements Serializable
    serialVersionUID:
      7751005204635320414L

    - #### Serialized Fields

      - ##### m_AttList_Irr

            boolean[] m_AttList_Irr

        array defines which attributes are irrelevant, with: true = attribute is irrelevant; false = attribute is not irrelevant

      - ##### m_DecisionList

            ArrayList<weka.datagenerators.classifiers.classification.RDG1.RuleList> m_DecisionList

        decision list

      - ##### m_MaxRuleSize

            int m_MaxRuleSize

        maximum rule size

      - ##### m_MinRuleSize

            int m_MinRuleSize

        minimum rule size

      - ##### m_NumAttributes

            int m_NumAttributes

        Number of attribute the dataset should have

      - ##### m_NumClasses

            int m_NumClasses

        Number of Classes the dataset should have

      - ##### m_NumIrrelevant

            int m_NumIrrelevant

        number of irrelevant attributes.

      - ##### m_NumNumeric

            int m_NumNumeric

        number of numeric attribute

      - ##### m_VoteFlag

            boolean m_VoteFlag

        flag that stores if voting is wished

- ## Package weka.datagenerators.classifiers.regression

  - ### Class weka.datagenerators.classifiers.regression.Expression

    class Expression extends MexicanHat implements Serializable
    serialVersionUID:
      -4237047357682277211L

    - #### Serialized Fields

      - ##### m_Expression

            String m_Expression

        the expression for computing y

      - ##### m_Filter

            AddExpression m_Filter

        the filter for generating y out of x

      - ##### m_RawData

            Instances m_RawData

        the input data structure for the filter

  - ### Class weka.datagenerators.classifiers.regression.MexicanHat

    class MexicanHat extends RegressionGenerator implements Serializable
    serialVersionUID:
      4577016375261512975L

    - #### Serialized Fields

      - ##### m_Amplitude

            double m_Amplitude

        the amplitude of y

      - ##### m_MaxRange

            double m_MaxRange

        the upper boundary of the range, x is drawn from

      - ##### m_MinRange

            double m_MinRange

        the lower boundary of the range, x is drawn from

      - ##### m_NoiseRandom

            Random m_NoiseRandom

        the random number generator for the noise

      - ##### m_NoiseRate

            double m_NoiseRate

        the rate of the gaussian noise

      - ##### m_NoiseVariance

            double m_NoiseVariance

        the variance of the gaussian noise

- ## Package weka.datagenerators.clusterers

  - ### Class weka.datagenerators.clusterers.BIRCHCluster

    class BIRCHCluster extends ClusterGenerator implements Serializable
    serialVersionUID:
      -334820527230755027L

    - #### Serialized Fields

      - ##### m_ClusterList

            ArrayList<weka.datagenerators.clusterers.BIRCHCluster.Cluster> m_ClusterList

        cluster list

      - ##### m_DistMult

            double m_DistMult

        distance multiplier (option M)

      - ##### m_GridSize

            int m_GridSize

        grid size

      - ##### m_GridWidth

            double m_GridWidth

        grid width

      - ##### m_InputOrder

            int m_InputOrder

        input order (changed with option O)

      - ##### m_MaxInstNum

            int m_MaxInstNum

        maximal number of instances per cluster (option N)

      - ##### m_MaxRadius

            double m_MaxRadius

        maximum radius (option R)

      - ##### m_MinInstNum

            int m_MinInstNum

        minimal number of instances per cluster (option N)

      - ##### m_MinRadius

            double m_MinRadius

        minimum radius (option R)

      - ##### m_NumClusters

            int m_NumClusters

        Number of Clusters the dataset should have

      - ##### m_NumCycles

            int m_NumCycles

        number of cycles (option C)

      - ##### m_Pattern

            int m_Pattern

        pattern (changed with options G or S)

  - ### Class weka.datagenerators.clusterers.SubspaceCluster

    class SubspaceCluster extends ClusterGenerator implements Serializable
    serialVersionUID:
      -3454999858505621128L

    - #### Serialized Fields

      - ##### m_booleanCols

            Range m_booleanCols

        Stores which columns are boolean (default numeric)

      - ##### m_Clusters

            ClusterDefinition[] m_Clusters

        cluster list

      - ##### m_nominalCols

            Range m_nominalCols

        Stores which columns are nominal (default numeric)

      - ##### m_numValues

            int[] m_numValues

        if nominal, store number of values

  - ### Class weka.datagenerators.clusterers.SubspaceClusterDefinition

    class SubspaceClusterDefinition extends ClusterDefinition implements Serializable
    serialVersionUID:
      3135678125044007231L

    - #### Serialized Fields

      - ##### m_attributes

            boolean[] m_attributes

        attributes of this cluster

      - ##### m_AttrIndexRange

            Range m_AttrIndexRange

        range of atttributes

      - ##### m_attrIndices

            int[] m_attrIndices

        global indices of the attributes of the cluster

      - ##### m_clustersubtype

            int m_clustersubtype

        cluster subtypes

      - ##### m_clustertype

            int m_clustertype

        cluster type

      - ##### m_MaxInstNum

            int m_MaxInstNum

        maximal number of instances for this cluster

      - ##### m_MinInstNum

            int m_MinInstNum

        minimal number of instances for this cluster

      - ##### m_numClusterAttributes

            int m_numClusterAttributes

        number of attributes the cluster is defined for

      - ##### m_numInstances

            int m_numInstances

        number of instances for this cluster

      - ##### m_valueA

            double[] m_valueA

        min or mean

      - ##### m_valueB

            double[] m_valueB

        max or stddev

      - ##### m_valuesList

            String m_valuesList

        the specification of the list of values as a string

- ## Package weka.estimators

  - ### Class weka.estimators.DiscreteEstimator

    class DiscreteEstimator extends Estimator implements Serializable
    serialVersionUID:
      -5526486742612434779L

    - #### Serialized Fields

      - ##### m_Counts

            double[] m_Counts

        Hold the counts

      - ##### m_FPrior

            double m_FPrior

        Initialization for counts

      - ##### m_SumOfCounts

            double m_SumOfCounts

        Hold the sum of counts

  - ### Class weka.estimators.Estimator

    class Estimator extends Object implements Serializable
    serialVersionUID:
      -5902411487362274342L

    - #### Serialized Fields

      - ##### m_classValueIndex

            double m_classValueIndex

        The class value index is > -1 if subset is taken with specific class value only

      - ##### m_Debug

            boolean m_Debug

        Debugging mode

      - ##### m_DoNotCheckCapabilities

            boolean m_DoNotCheckCapabilities

        Whether capabilities should not be checked

      - ##### m_noClass

            boolean m_noClass

        set if class is not important

  - ### Class weka.estimators.KernelEstimator

    class KernelEstimator extends Estimator implements Serializable
    serialVersionUID:
      3646923563367683925L

    - #### Serialized Fields

      - ##### m_AllWeightsOne

            boolean m_AllWeightsOne

        Whether we can optimise the kernel summation

      - ##### m_NumValues

            int m_NumValues

        Number of values stored in m_Weights and m_Values so far

      - ##### m_Precision

            double m_Precision

        The precision of data values

      - ##### m_StandardDev

            double m_StandardDev

        The standard deviation

      - ##### m_SumOfWeights

            double m_SumOfWeights

        The sum of the weights so far

      - ##### m_Values

            double[] m_Values

        Vector containing all of the values seen

      - ##### m_Weights

            double[] m_Weights

        Vector containing the associated weights

  - ### Class weka.estimators.MahalanobisEstimator

    class MahalanobisEstimator extends Estimator implements Serializable
    serialVersionUID:
      8950225468990043868L

    - #### Serialized Fields

      - ##### m_ConstDelta

            double m_ConstDelta

        The difference between the conditioning value and the conditioning mean

      - ##### m_CovarianceInverse

            Matrix m_CovarianceInverse

        The inverse of the covariance matrix

      - ##### m_Determinant

            double m_Determinant

        The determinant of the covariance matrix

      - ##### m_ValueMean

            double m_ValueMean

        The mean of the values

  - ### Class weka.estimators.MultivariateGaussianEstimator

    class MultivariateGaussianEstimator extends Object implements Serializable

    - #### Serialized Fields

      - ##### covarianceInverse

            no.uib.cipr.matrix.UpperSPDDenseMatrix covarianceInverse

        Inverse of covariance matrix

      - ##### lnconstant

            double lnconstant

        Factor to make density integrate to one (log of this factor)

      - ##### m_Ridge

            double m_Ridge

        Ridge parameter to add to diagonal of covariance matrix

      - ##### mean

            no.uib.cipr.matrix.DenseVector mean

        Mean vector

  - ### Class weka.estimators.NormalEstimator

    class NormalEstimator extends Estimator implements Serializable
    serialVersionUID:
      93584379632315841L

    - #### Serialized Fields

      - ##### m_Mean

            double m_Mean

        The current mean

      - ##### m_Precision

            double m_Precision

        The precision of numeric values ( = minimum std dev permitted)

      - ##### m_StandardDev

            double m_StandardDev

        The current standard deviation

      - ##### m_SumOfValues

            double m_SumOfValues

        The sum of the values seen

      - ##### m_SumOfValuesSq

            double m_SumOfValuesSq

        The sum of the values squared

      - ##### m_SumOfWeights

            double m_SumOfWeights

        The sum of the weights

  - ### Class weka.estimators.PoissonEstimator

    class PoissonEstimator extends Estimator implements Serializable
    serialVersionUID:
      7669362595289236662L

    - #### Serialized Fields

      - ##### m_Lambda

            double m_Lambda

        The average number of times an event occurs in an interval.

      - ##### m_NumValues

            double m_NumValues

        The number of values seen

      - ##### m_SumOfValues

            double m_SumOfValues

        The sum of the values seen

  - ### Class weka.estimators.UnivariateEqualFrequencyHistogramEstimator

    class UnivariateEqualFrequencyHistogramEstimator extends Object implements Serializable
    serialVersionUID:
      -3180287591539683137L

    - #### Serialized Fields

      - ##### m_Boundaries

            double[] m_Boundaries

        The interval boundaries.

      - ##### m_Exponent

            double m_Exponent

        The exponent to use in computation of bandwidth (default: -0.25)

      - ##### m_MinWidth

            double m_MinWidth

        The minimum allowed value of the kernel width (default: 1.0E-6)

      - ##### m_NumBins

            int m_NumBins

        The number of bins to use.

      - ##### m_NumIntervals

            int m_NumIntervals

        The number of intervals used to approximate prediction interval.

      - ##### m_SumOfWeights

            double m_SumOfWeights

        The total sum of weights.

      - ##### m_TM

            TreeMap<Double,Double> m_TM

        The collection used to store the weighted values.

      - ##### m_UpdateWeightsOnly

            boolean m_UpdateWeightsOnly

        Whether boundaries are updated or only weights.

      - ##### m_WeightedSum

            double m_WeightedSum

        The weighted sum of values

      - ##### m_WeightedSumSquared

            double m_WeightedSumSquared

        The weighted sum of squared values

      - ##### m_Weights

            double[] m_Weights

        The weight of each interval.

      - ##### m_Width

            double m_Width

        The current bandwidth (only computed when needed)

  - ### Class weka.estimators.UnivariateKernelEstimator

    class UnivariateKernelEstimator extends Object implements Serializable
    serialVersionUID:
      -1163983347810498880L

    - #### Serialized Fields

      - ##### m_Exponent

            double m_Exponent

        The exponent to use in computation of bandwidth (default: -0.25)

      - ##### m_MinWidth

            double m_MinWidth

        The minimum allowed value of the kernel width (default: 1.0E-6)

      - ##### m_NumIntervals

            int m_NumIntervals

        The number of intervals used to approximate prediction interval.

      - ##### m_SumOfWeights

            double m_SumOfWeights

        The weight of the values collected so far

      - ##### m_Threshold

            double m_Threshold

        Threshold at which further kernels are no longer added to sum.

      - ##### m_TM

            TreeMap<Double,Double> m_TM

        The collection used to store the weighted values.

      - ##### m_WeightedSum

            double m_WeightedSum

        The weighted sum of values

      - ##### m_WeightedSumSquared

            double m_WeightedSumSquared

        The weighted sum of squared values

      - ##### m_Width

            double m_Width

        The current bandwidth (only computed when needed)

  - ### Class weka.estimators.UnivariateMixtureEstimator

    class UnivariateMixtureEstimator extends Object implements Serializable
    serialVersionUID:
      -2035274930137353656L

    - #### Serialized Fields

      - ##### m_Debug

            boolean m_Debug

        Whether to output debug info.

      - ##### m_MaxNumComponents

            int m_MaxNumComponents

        The maximum number of components to use (default is 5)

      - ##### m_MixtureModel

            UnivariateMixtureEstimator.MM m_MixtureModel

        The current mixture model

      - ##### m_NumBootstrapRuns

            int m_NumBootstrapRuns

        The number of Bootstrap runs to use to select the number of components (default is 10)

      - ##### m_NumComponents

            int m_NumComponents

        The number of components to use (default is -1)

      - ##### m_NumIntervals

            int m_NumIntervals

        The number of intervals used to approximate prediction interval.

      - ##### m_NumValues

            int m_NumValues

        The number of values that have been seen

      - ##### m_Random

            Random m_Random

        The random number generator.

      - ##### m_Seed

            int m_Seed

        The random number seed to use (default is 1

      - ##### m_UseNormalizedEntropy

            boolean m_UseNormalizedEntropy

        Whether to use normalized entropy instance of bootstrap.

      - ##### m_Values

            double[] m_Values

        The values used for this estimator

      - ##### m_Weights

            double[] m_Weights

        The weights used for this estimator

  - ### Class weka.estimators.UnivariateNormalEstimator

    class UnivariateNormalEstimator extends Object implements Serializable
    serialVersionUID:
      -1669009817825826548L

    - #### Serialized Fields

      - ##### m_Mean

            double m_Mean

        The mean value (only updated when needed)

      - ##### m_MinVar

            double m_MinVar

        The minimum allowed value of the variance (default: 1.0E-6 * 1.0E-6)

      - ##### m_SumOfWeights

            double m_SumOfWeights

        The weight of the values collected so far

      - ##### m_Variance

            double m_Variance

        The variance (only updated when needed)

      - ##### m_WeightedSum

            double m_WeightedSum

        The weighted sum of values

      - ##### m_WeightedSumSquared

            double m_WeightedSumSquared

        The weighted sum of squared values

- ## Package weka.experiment

  - ### Class weka.experiment.AveragingResultProducer

    class AveragingResultProducer extends Object implements Serializable
    serialVersionUID:
      2551284958501991352L

    - #### Serialized Fields

      - ##### m_AdditionalMeasures

            String[] m_AdditionalMeasures

        The names of any additional measures to look for in SplitEvaluators

      - ##### m_CalculateStdDevs

            boolean m_CalculateStdDevs

        True if standard deviation fields should be produced

      - ##### m_CountFieldName

            String m_CountFieldName

        The name of the field that will contain the number of results averaged over.

      - ##### m_ExpectedResultsPerAverage

            int m_ExpectedResultsPerAverage

        The number of results expected to average over for each run

      - ##### m_Instances

            Instances m_Instances

        The dataset of interest

      - ##### m_KeyFieldName

            String m_KeyFieldName

        The name of the key field to average over

      - ##### m_KeyIndex

            int m_KeyIndex

        The index of the field to average over in the resultproducers key

      - ##### m_Keys

            ArrayList<Object[]> m_Keys

        Collects the keys from a single run

      - ##### m_ResultListener

            ResultListener m_ResultListener

        The ResultListener to send results to

      - ##### m_ResultProducer

            ResultProducer m_ResultProducer

        The ResultProducer used to generate results

      - ##### m_Results

            ArrayList<Object[]> m_Results

        Collects the results from a single run

  - ### Class weka.experiment.ClassifierSplitEvaluator

    class ClassifierSplitEvaluator extends Object implements Serializable
    serialVersionUID:
      -8511241602760467265L

    - #### Serialized Fields

      - ##### m_AdditionalMeasures

            String[] m_AdditionalMeasures

        The names of any additional measures to look for in SplitEvaluators

      - ##### m_attID

            int m_attID

        Attribute index of instance identifier (default -1)

      - ##### m_Classifier

            Classifier m_Classifier

        The classifier used for evaluation

      - ##### m_ClassifierOptions

            String m_ClassifierOptions

        The classifier options (if any)

      - ##### m_ClassifierVersion

            String m_ClassifierVersion

        The classifier version

      - ##### m_doesProduce

            boolean[] m_doesProduce

        Array of booleans corresponding to the measures in m_AdditionalMeasures indicating which of the AdditionalMeasures the current classifier can produce

      - ##### m_Evaluation

            Evaluation m_Evaluation

        Holds the most recently used Evaluation object

      - ##### m_IRclass

            int m_IRclass

        Class index for information retrieval statistics (default 0)

      - ##### m_NoSizeDetermination

            boolean m_NoSizeDetermination

        whether to skip determination of sizes (train/test/classifier).

      - ##### m_numberAdditionalMeasures

            int m_numberAdditionalMeasures

        The number of additional measures that need to be filled in after taking into account column constraints imposed by the final destination for results

      - ##### m_numPluginStatistics

            int m_numPluginStatistics

      - ##### m_pluginMetrics

            List<AbstractEvaluationMetric> m_pluginMetrics

      - ##### m_predTargetColumn

            boolean m_predTargetColumn

        Flag for prediction and target columns output.

      - ##### m_result

            String m_result

        Holds the statistics for the most recent application of the classifier

      - ##### m_Template

            Classifier m_Template

        The template classifier

  - ### Class weka.experiment.CostSensitiveClassifierSplitEvaluator

    class CostSensitiveClassifierSplitEvaluator extends ClassifierSplitEvaluator implements Serializable
    serialVersionUID:
      -8069566663019501276L

    - #### Serialized Fields

      - ##### m_OnDemandDirectory

            File m_OnDemandDirectory

        The directory used when loading cost files on demand, null indicates current directory

  - ### Class weka.experiment.CrossValidationResultProducer

    class CrossValidationResultProducer extends Object implements Serializable
    serialVersionUID:
      -1580053925080091917L

    - #### Serialized Fields

      - ##### m_AdditionalMeasures

            String[] m_AdditionalMeasures

        The names of any additional measures to look for in SplitEvaluators

      - ##### m_debugOutput

            boolean m_debugOutput

        Save raw output of split evaluators --- for debugging purposes

      - ##### m_Instances

            Instances m_Instances

        The dataset of interest

      - ##### m_NumFolds

            int m_NumFolds

        The number of folds in the cross-validation

      - ##### m_OutputFile

            File m_OutputFile

        The destination output file/directory for raw output

      - ##### m_ResultListener

            ResultListener m_ResultListener

        The ResultListener to send results to

      - ##### m_SplitEvaluator

            SplitEvaluator m_SplitEvaluator

        The SplitEvaluator used to generate results

      - ##### m_ZipDest

            OutputZipper m_ZipDest

        The output zipper to use for saving raw splitEvaluator output

  - ### Class weka.experiment.CrossValidationSplitResultProducer

    class CrossValidationSplitResultProducer extends CrossValidationResultProducer implements Serializable
    serialVersionUID:
      1403798164046795073L

  - ### Class weka.experiment.CSVResultListener

    class CSVResultListener extends Object implements Serializable
    serialVersionUID:
      -623185072785174658L

    - #### Serialized Fields

      - ##### m_OutputFile

            File m_OutputFile

        The destination output file, null sends to System.out

      - ##### m_OutputFileName

            String m_OutputFileName

        The name of the output file. Empty for temporary file.

      - ##### m_RP

            ResultProducer m_RP

        The ResultProducer sending us results

  - ### Class weka.experiment.DatabaseResultListener

    class DatabaseResultListener extends DatabaseUtils implements Serializable
    serialVersionUID:
      7388014746954652818L

    - #### Serialized Fields

      - ##### m_Cache

            ArrayList<String> m_Cache

        Stores the cached values

      - ##### m_CacheKey

            Object[] m_CacheKey

        Stores the key for which the cache is valid

      - ##### m_CacheKeyIndex

            int m_CacheKeyIndex

        Stores the index of the key column holding the cache key data

      - ##### m_CacheKeyName

            String m_CacheKeyName

        Holds the name of the key field to cache upon, or null if no caching

      - ##### m_ResultProducer

            ResultProducer m_ResultProducer

        The ResultProducer to listen to

      - ##### m_ResultsTableName

            String m_ResultsTableName

        The name of the current results table

  - ### Class weka.experiment.DatabaseResultProducer

    class DatabaseResultProducer extends DatabaseResultListener implements Serializable
    serialVersionUID:
      -5620660780203158666L

    - #### Serialized Fields

      - ##### m_AdditionalMeasures

            String[] m_AdditionalMeasures

        The names of any additional measures to look for in SplitEvaluators

      - ##### m_Instances

            Instances m_Instances

        The dataset of interest

      - ##### m_ResultListener

            ResultListener m_ResultListener

        The ResultListener to send results to

  - ### Class weka.experiment.DatabaseUtils

    class DatabaseUtils extends Object implements Serializable
    serialVersionUID:
      -8252351994547116729L

    - #### Serialized Fields

      - ##### DRIVERS

            Vector<String> DRIVERS

        Holds the jdbc drivers to be used (only to stop them being gc'ed).

      - ##### m_checkForLowerCaseNames

            boolean m_checkForLowerCaseNames

        For databases where Tables and Columns are created in lower case.

      - ##### m_checkForUpperCaseNames

            boolean m_checkForUpperCaseNames

        For databases where Tables and Columns are created in upper case.

      - ##### m_createIndex

            boolean m_createIndex

        create index on the database?

      - ##### m_DatabaseURL

            String m_DatabaseURL

        Database URL.

      - ##### m_Debug

            boolean m_Debug

        True if debugging output should be printed.

      - ##### m_doubleType

            String m_doubleType

        double type for the create table statement.

      - ##### m_intType

            String m_intType

        integer type for the create table statement.

      - ##### m_Keywords

            HashSet<String> m_Keywords

        the keywords for the current database type.

      - ##### m_KeywordsMaskChar

            String m_KeywordsMaskChar

        the character to mask SQL keywords (by appending this character).

      - ##### m_password

            String m_password

        Database Password.

      - ##### m_setAutoCommit

            boolean m_setAutoCommit

        setAutoCommit on the database?

      - ##### m_stringType

            String m_stringType

        string type for the create table statement.

      - ##### m_userName

            String m_userName

        Database username.

      - ##### PROPERTIES

            Properties PROPERTIES

        Properties associated with the database connection.

  - ### Class weka.experiment.DensityBasedClustererSplitEvaluator

    class DensityBasedClustererSplitEvaluator extends Object implements Serializable
    serialVersionUID:
      5124501059135692160L

    - #### Serialized Fields

      - ##### m_additionalMeasures

            String[] m_additionalMeasures

        The names of any additional measures to look for in SplitEvaluators

      - ##### m_clusterer

            DensityBasedClusterer m_clusterer

        The clusterer used for evaluation

      - ##### m_clustererOptions

            String m_clustererOptions

        The clusterer options (if any)

      - ##### m_clustererVersion

            String m_clustererVersion

        The clusterer version

      - ##### m_doesProduce

            boolean[] m_doesProduce

        Array of booleans corresponding to the measures in m_AdditionalMeasures indicating which of the AdditionalMeasures the current clusterer can produce

      - ##### m_Evaluation

            ClusterEvaluation m_Evaluation

        Holds the most recently used ClusterEvaluation object

      - ##### m_NoSizeDetermination

            boolean m_NoSizeDetermination

        whether to skip determination of sizes (train/test/classifier).

      - ##### m_numberAdditionalMeasures

            int m_numberAdditionalMeasures

        The number of additional measures that need to be filled in after taking into account column constraints imposed by the final destination for results

      - ##### m_removeClassColumn

            boolean m_removeClassColumn

        Remove the class column (if set) from the data

      - ##### m_result

            String m_result

        Holds the statistics for the most recent application of the clusterer

  - ### Class weka.experiment.Experiment

    class Experiment extends Object implements Serializable
    serialVersionUID:
      44945596742646663L

    - #### Serialized Fields

      - ##### m_AdditionalMeasures

            String[] m_AdditionalMeasures

        Method names of additional measures of objects contained in the custom property iterator. Only methods names beginning with "measure" and returning doubles are recognised

      - ##### m_AdvanceDataSetFirst

            boolean m_AdvanceDataSetFirst

        If true an experiment will advance the current data set befor any custom itererator

      - ##### m_ClassFirst

            boolean m_ClassFirst

        True if the class attribute is the first attribute for all datasets involved in this experiment.

      - ##### m_Datasets

            DefaultListModel m_Datasets

        An array of dataset files

      - ##### m_Notes

            String m_Notes

        User notes about the experiment

      - ##### m_PropertyArray

            Object m_PropertyArray

        The array of values to set the property to

      - ##### m_PropertyPath

            PropertyNode[] m_PropertyPath

        The path to the iterator property

      - ##### m_ResultListener

            ResultListener m_ResultListener

        Where results will be sent

      - ##### m_ResultProducer

            ResultProducer m_ResultProducer

        The result producer

      - ##### m_RunLower

            int m_RunLower

        Lower run number

      - ##### m_RunUpper

            int m_RunUpper

        Upper run number

      - ##### m_UsePropertyIterator

            boolean m_UsePropertyIterator

        True if the exp should also iterate over a property of the RP

  - ### Class weka.experiment.ExplicitTestsetResultProducer

    class ExplicitTestsetResultProducer extends Object implements Serializable
    serialVersionUID:
      2613585409333652530L

    - #### Serialized Fields

      - ##### m_AdditionalMeasures

            String[] m_AdditionalMeasures

        The names of any additional measures to look for in SplitEvaluators.

      - ##### m_debugOutput

            boolean m_debugOutput

        Save raw output of split evaluators --- for debugging purposes.

      - ##### m_Instances

            Instances m_Instances

        The dataset of interest.

      - ##### m_OutputFile

            File m_OutputFile

        The destination output file/directory for raw output.

      - ##### m_randomize

            boolean m_randomize

        Whether dataset is to be randomized.

      - ##### m_RelationFind

            String m_RelationFind

        The regular expression to search for in the relation name.

      - ##### m_RelationReplace

            String m_RelationReplace

        The string to use to replace the matches of the regular expression.

      - ##### m_ResultListener

            ResultListener m_ResultListener

        The ResultListener to send results to.

      - ##### m_SplitEvaluator

            SplitEvaluator m_SplitEvaluator

        The SplitEvaluator used to generate results.

      - ##### m_TestsetDir

            File m_TestsetDir

        The directory containing all the test sets.

      - ##### m_TestsetPrefix

            String m_TestsetPrefix

        The prefix for all the test sets.

      - ##### m_TestsetSuffix

            String m_TestsetSuffix

        The suffix for all the test sets.

      - ##### m_ZipDest

            OutputZipper m_ZipDest

        The output zipper to use for saving raw splitEvaluator output.

  - ### Class weka.experiment.InstanceQuery

    class InstanceQuery extends DatabaseUtils implements Serializable
    serialVersionUID:
      718158370917782584L

    - #### Serialized Fields

      - ##### m_CreateSparseData

            boolean m_CreateSparseData

        Determines whether sparse data is created

      - ##### m_CustomPropsFile

            File m_CustomPropsFile

        the custom props file to use instead of default one.

      - ##### m_Query

            String m_Query

        Query to execute

  - ### Class weka.experiment.InstancesResultListener

    class InstancesResultListener extends CSVResultListener implements Serializable
    serialVersionUID:
      -2203808461809311178L

  - ### Class weka.experiment.LearningRateResultProducer

    class LearningRateResultProducer extends Object implements Serializable
    serialVersionUID:
      -3841159673490861331L

    - #### Serialized Fields

      - ##### m_AdditionalMeasures

            String[] m_AdditionalMeasures

        The names of any additional measures to look for in SplitEvaluators

      - ##### m_CurrentSize

            int m_CurrentSize

        The current dataset size during stepping

      - ##### m_Instances

            Instances m_Instances

        The dataset of interest

      - ##### m_LowerSize

            int m_LowerSize

        The minimum number of instances to use. If this is zero, the first step will contain m_StepSize instances

      - ##### m_ResultListener

            ResultListener m_ResultListener

        The ResultListener to send results to

      - ##### m_ResultProducer

            ResultProducer m_ResultProducer

        The ResultProducer used to generate results

      - ##### m_StepSize

            int m_StepSize

        The number of instances to add at each step

      - ##### m_UpperSize

            int m_UpperSize

        The maximum number of instances to use. -1 indicates no maximum (other than the total number of instances)

  - ### Class weka.experiment.PairedCorrectedTTester

    class PairedCorrectedTTester extends PairedTTester implements Serializable
    serialVersionUID:
      -3105268939845653323L

  - ### Class weka.experiment.PairedTTester

    class PairedTTester extends Object implements Serializable
    serialVersionUID:
      8370014624008728610L

    - #### Serialized Fields

      - ##### m_ColOrder

            int[] m_ColOrder

        The sorting of the columns (test base is always first)

      - ##### m_DatasetKeyColumns

            int[] m_DatasetKeyColumns

        An array containing the indexes of just the selected columns

      - ##### m_DatasetKeyColumnsRange

            Range m_DatasetKeyColumnsRange

        The range of columns that specify a unique "dataset" (eg: scheme plus configuration)

      - ##### m_DatasetSpecifiers

            weka.experiment.PairedTTester.DatasetSpecifiers m_DatasetSpecifiers

        The list of dataset specifiers

      - ##### m_DisplayedResultsets

            int[] m_DisplayedResultsets

        An array containing the indexes of the datasets to display

      - ##### m_FoldColumn

            int m_FoldColumn

        The option setting for the fold number column (-1 means none)

      - ##### m_Instances

            Instances m_Instances

        The set of instances we will analyse

      - ##### m_ResultMatrix

            ResultMatrix m_ResultMatrix

        the instance of the class to produce the output.

      - ##### m_ResultsetKeyColumns

            int[] m_ResultsetKeyColumns

        An array containing the indexes of just the selected columns

      - ##### m_ResultsetKeyColumnsRange

            Range m_ResultsetKeyColumnsRange

        The range of columns that specify a unique result set (eg: scheme plus configuration)

      - ##### m_Resultsets

            ArrayList<weka.experiment.PairedTTester.Resultset> m_Resultsets

        Stores a vector for each resultset holding all instances in each set

      - ##### m_ResultsetsValid

            boolean m_ResultsetsValid

        Indicates whether the instances have been partitioned

      - ##### m_RunColumn

            int m_RunColumn

        The index of the column containing the run number

      - ##### m_RunColumnSet

            int m_RunColumnSet

        The option setting for the run number column (-1 means last)

      - ##### m_ShowStdDevs

            boolean m_ShowStdDevs

        Indicates whether standard deviations should be displayed

      - ##### m_SignificanceLevel

            double m_SignificanceLevel

        The significance level for comparisons

      - ##### m_SortColumn

            int m_SortColumn

        The column to sort on (-1 means default sorting)

      - ##### m_SortOrder

            int[] m_SortOrder

        The sorting of the datasets (according to the sort column)

  - ### Class weka.experiment.PairedTTester.Dataset

    class Dataset extends Object implements Serializable
    serialVersionUID:
      -2801397601839433282L

    - #### Serialized Fields

      - ##### m_Dataset

            ArrayList<Instance> m_Dataset

        the dataset

      - ##### m_Template

            Instance m_Template

        the template

  - ### Class weka.experiment.PairedTTester.DatasetSpecifiers

    class DatasetSpecifiers extends Object implements Serializable
    serialVersionUID:
      -9020938059902723401L

    - #### Serialized Fields

      - ##### m_Specifiers

            ArrayList<Instance> m_Specifiers

        the specifiers that have been observed

  - ### Class weka.experiment.PairedTTester.Resultset

    class Resultset extends Object implements Serializable
    serialVersionUID:
      1543786683821339978L

    - #### Serialized Fields

      - ##### m_Datasets

            ArrayList<weka.experiment.PairedTTester.Dataset> m_Datasets

        the dataset

      - ##### m_Template

            Instance m_Template

        the template

  - ### Class weka.experiment.PropertyNode

    class PropertyNode extends Object implements Serializable
    serialVersionUID:
      -8718165742572631384L

    - #### Serialization Methods

      - ##### readObject

        private void readObject(ObjectInputStream in) throws IOException, ClassNotFoundException
        Throws:
          `IOException`
          `ClassNotFoundException`

      - ##### writeObject

        private void writeObject(ObjectOutputStream out) throws IOException
        Throws:
          `IOException`

    - #### Serialized Fields

      - ##### parentClass

            Class<?> parentClass

        The class of the object with this property

      - ##### property

            PropertyDescriptor property

        Other info about the property

      - ##### value

            Object value

        The current property value

  - ### Class weka.experiment.RandomSplitResultProducer

    class RandomSplitResultProducer extends Object implements Serializable
    serialVersionUID:
      1403798165056795073L

    - #### Serialized Fields

      - ##### m_AdditionalMeasures

            String[] m_AdditionalMeasures

        The names of any additional measures to look for in SplitEvaluators

      - ##### m_debugOutput

            boolean m_debugOutput

        Save raw output of split evaluators --- for debugging purposes

      - ##### m_Instances

            Instances m_Instances

        The dataset of interest

      - ##### m_OutputFile

            File m_OutputFile

        The destination output file/directory for raw output

      - ##### m_randomize

            boolean m_randomize

        Whether dataset is to be randomized

      - ##### m_ResultListener

            ResultListener m_ResultListener

        The ResultListener to send results to

      - ##### m_SplitEvaluator

            SplitEvaluator m_SplitEvaluator

        The SplitEvaluator used to generate results

      - ##### m_TrainPercent

            double m_TrainPercent

        The percentage of instances to use for training

      - ##### m_ZipDest

            OutputZipper m_ZipDest

        The output zipper to use for saving raw splitEvaluator output

  - ### Class weka.experiment.RegressionSplitEvaluator

    class RegressionSplitEvaluator extends Object implements Serializable
    serialVersionUID:
      -328181640503349202L

    - #### Serialized Fields

      - ##### m_AdditionalMeasures

            String[] m_AdditionalMeasures

        The names of any additional measures to look for in SplitEvaluators

      - ##### m_Classifier

            Classifier m_Classifier

        The classifier used for evaluation

      - ##### m_ClassifierOptions

            String m_ClassifierOptions

        The classifier options (if any)

      - ##### m_ClassifierVersion

            String m_ClassifierVersion

        The classifier version

      - ##### m_doesProduce

            boolean[] m_doesProduce

        Array of booleans corresponding to the measures in m_AdditionalMeasures indicating which of the AdditionalMeasures the current classifier can produce

      - ##### m_Evaluation

            Evaluation m_Evaluation

        Holds the most recently used Evaluation object

      - ##### m_NoSizeDetermination

            boolean m_NoSizeDetermination

        whether to skip determination of sizes (train/test/classifier).

      - ##### m_numPluginStatistics

            int m_numPluginStatistics

      - ##### m_pluginMetrics

            List<AbstractEvaluationMetric> m_pluginMetrics

      - ##### m_result

            String m_result

        Holds the statistics for the most recent application of the classifier

      - ##### m_Template

            Classifier m_Template

        The template classifier

  - ### Class weka.experiment.RemoteEngine

    class RemoteEngine extends UnicastRemoteObject implements Serializable
    serialVersionUID:
      -1021538162895448259L

    - #### Serialized Fields

      - ##### m_HostName

            String m_HostName

        The name of the host that this engine is started on

      - ##### m_TaskIdQueue

            Queue m_TaskIdQueue

        A queue of corresponding ID's for tasks

      - ##### m_TaskQueue

            Queue m_TaskQueue

        A queue of waiting tasks

      - ##### m_TaskRunning

            boolean m_TaskRunning

        Is there a task running

      - ##### m_TaskStatus

            Hashtable<String,TaskStatusInfo> m_TaskStatus

        A hashtable of experiment status

  - ### Class weka.experiment.RemoteExperiment

    class RemoteExperiment extends Experiment implements Serializable
    serialVersionUID:
      -7357668825635314937L

    - #### Serialized Fields

      - ##### m_baseExperiment

            Experiment m_baseExperiment

        The base experiment to split up into sub experiments for remote execution

      - ##### m_experimentAborted

            boolean m_experimentAborted

        Set to true if MAX_FAILURES exceeded on all hosts or connections fail on all hosts or user aborts experiment (via gui)

      - ##### m_failedCount

            int m_failedCount

        The count of failed sub-experiments

      - ##### m_finishedCount

            int m_finishedCount

        The count of successfully completed sub-experiments

      - ##### m_listeners

            ArrayList<RemoteExperimentListener> m_listeners

        The list of objects listening for remote experiment events

      - ##### m_remoteHostFailureCounts

            int[] m_remoteHostFailureCounts

        The number of times tasks have failed on each remote host

      - ##### m_remoteHosts

            DefaultListModel m_remoteHosts

        Holds the names of machines with remoteEngine servers running

      - ##### m_remoteHostsQueue

            Queue m_remoteHostsQueue

        The queue of available hosts

      - ##### m_remoteHostsStatus

            int[] m_remoteHostsStatus

        The status of each of the remote hosts

      - ##### m_removedHosts

            int m_removedHosts

        The number of hosts removed due to exceeding max failures

      - ##### m_splitByDataSet

            boolean m_splitByDataSet

        If true, then sub experiments are created on the basis of data sets.

      - ##### m_splitByProperty

            boolean m_splitByProperty

        If true, then sub experiments are created on the basis of properties

      - ##### m_subExpComplete

            int[] m_subExpComplete

        The status of each of the sub-experiments

      - ##### m_subExperiments

            Experiment[] m_subExperiments

        The sub experiments

      - ##### m_subExpQueue

            Queue m_subExpQueue

        The queue of sub experiments waiting to be processed

  - ### Class weka.experiment.RemoteExperimentEvent

    class RemoteExperimentEvent extends Object implements Serializable
    serialVersionUID:
      7000867987391866451L

    - #### Serialized Fields

      - ##### m_experimentFinished

            boolean m_experimentFinished

        True if a remote experiment has finished

      - ##### m_logMessage

            boolean m_logMessage

        A log type message

      - ##### m_messageString

            String m_messageString

        The message

      - ##### m_statusMessage

            boolean m_statusMessage

        A status type message

  - ### Class weka.experiment.RemoteExperimentSubTask

    class RemoteExperimentSubTask extends Object implements Serializable
    serialVersionUID:
      -1674092706571603720L

    - #### Serialized Fields

      - ##### m_experiment

            Experiment m_experiment

      - ##### m_result

            TaskStatusInfo m_result

      - ##### m_serializedExp

            SerializedObject m_serializedExp

  - ### Class weka.experiment.ResultMatrix

    class ResultMatrix extends Object implements Serializable
    serialVersionUID:
      4487179306428209739L

    - #### Serialized Fields

      - ##### LEFT_PARENTHESES

            String LEFT_PARENTHESES

        the left parentheses for enumerating cols/rows.

      - ##### LOSS_STRING

            String LOSS_STRING

        loss string.

      - ##### m_ColHidden

            boolean[] m_ColHidden

        whether a column is hidden.

      - ##### m_ColNames

            String[] m_ColNames

        the column names.

      - ##### m_ColNameWidth

            int m_ColNameWidth

        the size of the names of the columns.

      - ##### m_ColOrder

            int[] m_ColOrder

        the ordering of the columns.

      - ##### m_Counts

            double[] m_Counts

        the counts for the different datasets.

      - ##### m_CountWidth

            int m_CountWidth

        the size of the counts.

      - ##### m_EnumerateColNames

            boolean m_EnumerateColNames

        whether a "(x)" is printed before each column name with "x" as the index.

      - ##### m_EnumerateRowNames

            boolean m_EnumerateRowNames

        whether a "(x)" is printed before each row name with "x" as the index.

      - ##### m_HeaderKeys

            Vector<String> m_HeaderKeys

        contains the keys for the header.

      - ##### m_HeaderValues

            Vector<String> m_HeaderValues

        contains the values for the header.

      - ##### m_Mean

            double[][] m_Mean

        the values.

      - ##### m_MeanPrec

            int m_MeanPrec

        the standard mean precision.

      - ##### m_MeanWidth

            int m_MeanWidth

        the size of the mean columns.

      - ##### m_NonSigWins

            int[][] m_NonSigWins

        the non-significant wins.

      - ##### m_PrintColNames

            boolean m_PrintColNames

        whether the names or numbers are output as column declarations.

      - ##### m_PrintRowNames

            boolean m_PrintRowNames

        whether the names or numbers are output as row declarations.

      - ##### m_RankingDiff

            int[] m_RankingDiff

        the difference between wins and losses.

      - ##### m_RankingLosses

            int[] m_RankingLosses

        the losses in ranking.

      - ##### m_RankingWins

            int[] m_RankingWins

        the wins in ranking.

      - ##### m_RemoveFilterName

            boolean m_RemoveFilterName

        whether to remove the filter name from the dataaset name.

      - ##### m_RowHidden

            boolean[] m_RowHidden

        whether a row is hidden.

      - ##### m_RowNames

            String[] m_RowNames

        the row names.

      - ##### m_RowNameWidth

            int m_RowNameWidth

        the size of the names of the rows.

      - ##### m_RowOrder

            int[] m_RowOrder

        the ordering of the rows.

      - ##### m_ShowAverage

            boolean m_ShowAverage

        whether the average for each column should be printed.

      - ##### m_ShowStdDev

            boolean m_ShowStdDev

        whether std. deviations are printed as well.

      - ##### m_Significance

            int[][] m_Significance

        the significance.

      - ##### m_SignificanceWidth

            int m_SignificanceWidth

        the size of the significance columns.

      - ##### m_StdDev

            double[][] m_StdDev

        the standard deviation.

      - ##### m_StdDevPrec

            int m_StdDevPrec

        the standard std. deviation preicision.

      - ##### m_StdDevWidth

            int m_StdDevWidth

        the size of the std dev columns.

      - ##### m_Wins

            int[][] m_Wins

        the significant wins.

      - ##### RIGHT_PARENTHESES

            String RIGHT_PARENTHESES

        the right parentheses for enumerating cols/rows.

      - ##### TIE_STRING

            String TIE_STRING

        tie string.

      - ##### WIN_STRING

            String WIN_STRING

        win string.

  - ### Class weka.experiment.ResultMatrixCSV

    class ResultMatrixCSV extends ResultMatrix implements Serializable
    serialVersionUID:
      -171838863135042743L

  - ### Class weka.experiment.ResultMatrixGnuPlot

    class ResultMatrixGnuPlot extends ResultMatrix implements Serializable
    serialVersionUID:
      -234648254944790097L

  - ### Class weka.experiment.ResultMatrixHTML

    class ResultMatrixHTML extends ResultMatrix implements Serializable
    serialVersionUID:
      6672380422544799990L

  - ### Class weka.experiment.ResultMatrixLatex

    class ResultMatrixLatex extends ResultMatrix implements Serializable
    serialVersionUID:
      777690788447600978L

  - ### Class weka.experiment.ResultMatrixPlainText

    class ResultMatrixPlainText extends ResultMatrix implements Serializable
    serialVersionUID:
      1502934525382357937L

  - ### Class weka.experiment.ResultMatrixSignificance

    class ResultMatrixSignificance extends ResultMatrix implements Serializable
    serialVersionUID:
      -1280545644109764206L

  - ### Class weka.experiment.Stats

    class Stats extends Object implements Serializable
    serialVersionUID:
      -8610544539090024102L

    - #### Serialized Fields

      - ##### count

            double count

        The number of values seen

      - ##### max

            double max

        The maximum value seen, or Double.NaN if no values seen

      - ##### mean

            double mean

        The mean of values, or Double.NaN if no values seen

      - ##### min

            double min

        The minimum value seen, or Double.NaN if no values seen

      - ##### stdDev

            double stdDev

        The std deviation of values at the last calculateDerived() call

      - ##### stdDevFactor

            double stdDevFactor

        an important factor to calculate the standard deviation incrementally

      - ##### sum

            double sum

        The sum of values seen

      - ##### sumSq

            double sumSq

        The sum of values squared seen

  - ### Class weka.experiment.TaskStatusInfo

    class TaskStatusInfo extends Object implements Serializable
    serialVersionUID:
      -6129343303703560015L

    - #### Serialized Fields

      - ##### m_ExecutionStatus

            int m_ExecutionStatus

        Holds current execution status.

      - ##### m_StatusMessage

            String m_StatusMessage

        Holds current status message.

      - ##### m_TaskResult

            Object m_TaskResult

        Holds task result. Set to null for no returnable result.

- ## Package weka.filters

  - ### Class weka.filters.AllFilter

    class AllFilter extends Filter implements Serializable
    serialVersionUID:
      5022109283147503266L

  - ### Class weka.filters.Filter

    class Filter extends Object implements Serializable
    serialVersionUID:
      -8835063755891851218L

    - #### Serialized Fields

      - ##### m_Debug

            boolean m_Debug

        Whether the classifier is run in debug mode.

      - ##### m_DoNotCheckCapabilities

            boolean m_DoNotCheckCapabilities

        Whether capabilities should not be checked before classifier is built.

      - ##### m_FirstBatchDone

            boolean m_FirstBatchDone

        True if the first batch has been done

      - ##### m_InputFormat

            Instances m_InputFormat

        The input format for instances

      - ##### m_InputRelAtts

            RelationalLocator m_InputRelAtts

        Indices of relational attributes in the input format

      - ##### m_InputStringAtts

            StringLocator m_InputStringAtts

        Indices of string attributes in the input format

      - ##### m_NewBatch

            boolean m_NewBatch

        Record whether the filter is at the start of a batch

      - ##### m_OutputFormat

            Instances m_OutputFormat

        The output format for instances

      - ##### m_OutputQueue

            Queue m_OutputQueue

        The output instance queue

      - ##### m_OutputRelAtts

            RelationalLocator m_OutputRelAtts

        Indices of relational attributes in the output format

      - ##### m_OutputStringAtts

            StringLocator m_OutputStringAtts

        Indices of string attributes in the output format

  - ### Class weka.filters.MultiFilter

    class MultiFilter extends SimpleStreamFilter implements Serializable
    serialVersionUID:
      -6293720886005713120L

    - #### Serialized Fields

      - ##### m_Filters

            Filter[] m_Filters

        The filters

      - ##### m_Seed

            int m_Seed

        The random number seed that will be passed through to all filters that are randomizable.

      - ##### m_Streamable

            boolean m_Streamable

        caches the streamable state

      - ##### m_StreamableChecked

            boolean m_StreamableChecked

        whether we already checked the streamable state

  - ### Class weka.filters.RenameRelation

    class RenameRelation extends Filter implements Serializable
    serialVersionUID:
      8082179220141937043L

    - #### Serialized Fields

      - ##### m_modType

            weka.filters.RenameRelation.ModType m_modType

        The type of modification to make

      - ##### m_regexMatch

            String m_regexMatch

        Regex string to match

      - ##### m_regexPattern

            Pattern m_regexPattern

        Pattern for regex replacement

      - ##### m_relationNameModText

            String m_relationNameModText

        Text to modify the relation name with

      - ##### m_replaceAll

            boolean m_replaceAll

        Whether to replace all rexex matches, or just the first

  - ### Class weka.filters.SimpleBatchFilter

    class SimpleBatchFilter extends SimpleFilter implements Serializable
    serialVersionUID:
      8102908673378055114L

  - ### Class weka.filters.SimpleFilter

    class SimpleFilter extends Filter implements Serializable
    serialVersionUID:
      5702974949137433141L

  - ### Class weka.filters.SimpleStreamFilter

    class SimpleStreamFilter extends SimpleFilter implements Serializable
    serialVersionUID:
      2754882676192747091L

- ## Package weka.filters.supervised.attribute

  - ### Class weka.filters.supervised.attribute.AddClassification

    class AddClassification extends SimpleBatchFilter implements Serializable
    serialVersionUID:
      -1931467132568441909L

    - #### Serialized Fields

      - ##### m_ActualClassifier

            Classifier m_ActualClassifier

        The actual classifier used to do the classification.

      - ##### m_Classifier

            Classifier m_Classifier

        The classifier template used to do the classification.

      - ##### m_OutputClassification

            boolean m_OutputClassification

        whether to output the classification.

      - ##### m_OutputDistribution

            boolean m_OutputDistribution

        whether to output the class distribution.

      - ##### m_OutputErrorFlag

            boolean m_OutputErrorFlag

        whether to output the error flag.

      - ##### m_RemoveOldClass

            boolean m_RemoveOldClass

        whether to remove the old class attribute.

      - ##### m_SerializedClassifierFile

            File m_SerializedClassifierFile

        The file from which to load a serialized classifier.

      - ##### m_SerializedHeader

            Instances m_SerializedHeader

        the header of the file the serialized classifier was trained with.

  - ### Class weka.filters.supervised.attribute.AttributeSelection

    class AttributeSelection extends Filter implements Serializable
    serialVersionUID:
      -296211247688169716L

    - #### Serialized Fields

      - ##### m_ASEvaluator

            ASEvaluation m_ASEvaluator

        the attribute evaluator to use

      - ##### m_ASSearch

            ASSearch m_ASSearch

        the search method if any

      - ##### m_hasClass

            boolean m_hasClass

        True if a class attribute is set in the data

      - ##### m_SelectedAttributes

            int[] m_SelectedAttributes

        holds the selected attributes

      - ##### m_trainSelector

            AttributeSelection m_trainSelector

        the attribute selection evaluation object

  - ### Class weka.filters.supervised.attribute.ClassConditionalProbabilities

    class ClassConditionalProbabilities extends SimpleBatchFilter implements Serializable
    serialVersionUID:
      1684310720200284263L

    - #### Serialized Fields

      - ##### m_estimator

            NaiveBayes m_estimator

        The Naive Bayes classifier to use for class conditional estimation

      - ##### m_estimatorLookup

            Map<String,Estimator[]> m_estimatorLookup

        A lookup of estimators from Naive Bayes

      - ##### m_excludeNominalAttributes

            boolean m_excludeNominalAttributes

        True if nominal attributes are to be excluded from the transformation

      - ##### m_excludeNumericAttributes

            boolean m_excludeNumericAttributes

        True if numeric attributes are to be excluded from the transformation

      - ##### m_nominalConversionThreshold

            int m_nominalConversionThreshold

        Don't convert nominal attributes with fewer than this number of values. -1 means always convert

      - ##### m_remove

            Remove m_remove

        Remove filter to use for creating a set of untouched attributes

      - ##### m_SpreadAttributeWeight

            boolean m_SpreadAttributeWeight

        Whether to spread attribute weight when creating binary attributes

      - ##### m_unchanged

            Instances m_unchanged

        The attributes from the original data that are untouched by this transformation

  - ### Class weka.filters.supervised.attribute.ClassOrder

    class ClassOrder extends Filter implements Serializable
    serialVersionUID:
      -2116226838887628411L

    - #### Serialized Fields

      - ##### m_ClassAttribute

            Attribute m_ClassAttribute

        Class attribute of the data

      - ##### m_ClassCounts

            double[] m_ClassCounts

        This class can provide the class distribution in the sorted order as side effect

      - ##### m_ClassOrder

            int m_ClassOrder

        The class order to be sorted

      - ##### m_Converter

            int[] m_Converter

        The 1-1 converting table from the original class values to the new values

      - ##### m_Random

            Random m_Random

        The random object

      - ##### m_Seed

            long m_Seed

        The seed of randomization

  - ### Class weka.filters.supervised.attribute.Discretize

    class Discretize extends Filter implements Serializable
    serialVersionUID:
      -3141006402280129097L

    - #### Serialized Fields

      - ##### m_BinRangePrecision

            int m_BinRangePrecision

        Precision for bin range labels

      - ##### m_CutPoints

            double[][] m_CutPoints

        Store the current cutpoints

      - ##### m_DiscretizeCols

            Range m_DiscretizeCols

        Stores which columns to Discretize

      - ##### m_MakeBinary

            boolean m_MakeBinary

        Output binary attributes for discretized attributes.

      - ##### m_SpreadAttributeWeight

            boolean m_SpreadAttributeWeight

        Whether to spread attribute weight when creating binary attributes

      - ##### m_UseBetterEncoding

            boolean m_UseBetterEncoding

        Use better encoding of split point for MDL.

      - ##### m_UseBinNumbers

            boolean m_UseBinNumbers

        Use bin numbers rather than ranges for discretized attributes.

      - ##### m_UseKononenko

            boolean m_UseKononenko

        Use Kononenko's MDL criterion instead of Fayyad et al.'s

  - ### Class weka.filters.supervised.attribute.MergeNominalValues

    class MergeNominalValues extends SimpleBatchFilter implements Serializable
    serialVersionUID:
      7447337831221353842L

    - #### Serialized Fields

      - ##### m_AttToBeModified

            boolean[] m_AttToBeModified

        Indicators for which attributes need to be changed.

      - ##### m_Indicators

            int[][] m_Indicators

        The indicators used to map the old values.

      - ##### m_SelectCols

            Range m_SelectCols

        Stores which atributes to operate on (or nto)

      - ##### m_SelectedAttributes

            int[] m_SelectedAttributes

        Stores the indexes of the selected attributes in order.

      - ##### m_SigLevel

            double m_SigLevel

        Set the significance level

      - ##### m_UseShortIdentifiers

            boolean m_UseShortIdentifiers

        Use short values

  - ### Class weka.filters.supervised.attribute.NominalToBinary

    class NominalToBinary extends Filter implements Serializable
    serialVersionUID:
      -5004607029857673950L

    - #### Serialized Fields

      - ##### m_Indices

            int[][] m_Indices

        The sorted indices of the attribute values.

      - ##### m_needToTransform

            boolean m_needToTransform

        Whether we need to transform at all

      - ##### m_Numeric

            boolean m_Numeric

        Are the new attributes going to be nominal or numeric ones?

      - ##### m_SpreadAttributeWeight

            boolean m_SpreadAttributeWeight

        Whether to spread attribute weight when creating binary attributes

      - ##### m_TransformAll

            boolean m_TransformAll

        Are all values transformed into new attributes?

  - ### Class weka.filters.supervised.attribute.PartitionMembership

    class PartitionMembership extends Filter implements Serializable
    serialVersionUID:
      333532554667754026L

    - #### Serialized Fields

      - ##### m_partitionGenerator

            PartitionGenerator m_partitionGenerator

        The partition generator

- ## Package weka.filters.supervised.instance

  - ### Class weka.filters.supervised.instance.ClassBalancer

    class ClassBalancer extends SimpleBatchFilter implements Serializable
    serialVersionUID:
      6237337831221353842L

    - #### Serialized Fields

      - ##### m_NumIntervals

            int m_NumIntervals

        number of discretization intervals to use if the class is numeric

  - ### Class weka.filters.supervised.instance.Resample

    class Resample extends Filter implements Serializable
    serialVersionUID:
      7079064953548300681L

    - #### Serialized Fields

      - ##### m_BiasToUniformClass

            double m_BiasToUniformClass

        The degree of bias towards uniform (nominal) class distribution.

      - ##### m_InvertSelection

            boolean m_InvertSelection

        Whether to invert the selection (only if instances are drawn WITHOUT replacement).
        See Also:
          - `Resample.m_NoReplacement`

      - ##### m_NoReplacement

            boolean m_NoReplacement

        Whether to perform sampling with replacement or without.

      - ##### m_RandomSeed

            int m_RandomSeed

        The random number generator seed.

      - ##### m_SampleSizePercent

            double m_SampleSizePercent

        The subsample size, percent of original set, default 100%.

  - ### Class weka.filters.supervised.instance.SpreadSubsample

    class SpreadSubsample extends Filter implements Serializable
    serialVersionUID:
      -3947033795243930016L

    - #### Serialized Fields

      - ##### m_AdjustWeights

            boolean m_AdjustWeights

        True if instance weights will be adjusted to maintain total weight per class.

      - ##### m_DistributionSpread

            double m_DistributionSpread

        True if the first batch has been done

      - ##### m_MaxCount

            int m_MaxCount

        The maximum count of any class

      - ##### m_RandomSeed

            int m_RandomSeed

        The random number generator seed

  - ### Class weka.filters.supervised.instance.StratifiedRemoveFolds

    class StratifiedRemoveFolds extends Filter implements Serializable
    serialVersionUID:
      -7069148179905814324L

    - #### Serialized Fields

      - ##### m_Fold

            int m_Fold

        Fold to output

      - ##### m_Inverse

            boolean m_Inverse

        Indicates if inverse of selection is to be output.

      - ##### m_NumFolds

            int m_NumFolds

        Number of folds to split dataset into

      - ##### m_Seed

            long m_Seed

        Random number seed.

- ## Package weka.filters.unsupervised.attribute

  - ### Class weka.filters.unsupervised.attribute.AbstractTimeSeries

    class AbstractTimeSeries extends Filter implements Serializable
    serialVersionUID:
      -3795656792078022357L

    - #### Serialized Fields

      - ##### m_FillWithMissing

            boolean m_FillWithMissing

        True if missing values should be used rather than removing instances where the translated value is not known (due to border effects).

      - ##### m_History

            Queue m_History

        Stores the historical instances to copy values between

      - ##### m_InstanceRange

            int m_InstanceRange

        The number of instances forward to translate values between. A negative number indicates taking values from a past instance.

      - ##### m_SelectedCols

            Range m_SelectedCols

        Stores which columns to copy

  - ### Class weka.filters.unsupervised.attribute.Add

    class Add extends Filter implements Serializable
    serialVersionUID:
      761386447332932389L

    - #### Serialized Fields

      - ##### m_AttributeType

            int m_AttributeType

        Record the type of attribute to insert.

      - ##### m_DateFormat

            String m_DateFormat

        The date format.

      - ##### m_Insert

            SingleIndex m_Insert

        The location to insert the new attribute.

      - ##### m_Labels

            ArrayList<String> m_Labels

        The list of labels for nominal attribute.

      - ##### m_Name

            String m_Name

        The name for the new attribute.

      - ##### m_Weight

            double m_Weight

        The weight for the new attribute.

  - ### Class weka.filters.unsupervised.attribute.AddCluster

    class AddCluster extends Filter implements Serializable
    serialVersionUID:
      7414280611943807337L

    - #### Serialized Fields

      - ##### m_ActualClusterer

            Clusterer m_ActualClusterer

        The actual clusterer used to do the clustering.

      - ##### m_Clusterer

            Clusterer m_Clusterer

        The clusterer used to do the cleansing.

      - ##### m_IgnoreAttributesRange

            Range m_IgnoreAttributesRange

        Range of attributes to ignore.

      - ##### m_removeAttributes

            Filter m_removeAttributes

        Filter for removing attributes.

      - ##### m_SerializedClustererFile

            File m_SerializedClustererFile

        The file from which to load a serialized clusterer.

  - ### Class weka.filters.unsupervised.attribute.AddExpression

    class AddExpression extends Filter implements Serializable
    serialVersionUID:
      402130384261736245L

    - #### Serialized Fields

      - ##### m_attributeName

            String m_attributeName

        Name of the new attribute. "expression" length string will use the provided expression as the new attribute name

      - ##### m_Debug

            boolean m_Debug

        If true, makes the attribute name equal to the postfix parse of the expression

      - ##### m_Expression

            Primitives.DoubleExpression m_Expression

      - ##### m_infixExpression

            String m_infixExpression

        The infix expression

      - ##### m_InstancesHelper

            InstancesHelper m_InstancesHelper

  - ### Class weka.filters.unsupervised.attribute.AddID

    class AddID extends Filter implements Serializable
    serialVersionUID:
      4734383199819293390L

    - #### Serialized Fields

      - ##### m_Counter

            int m_Counter

        the counter for the ID

      - ##### m_Index

            SingleIndex m_Index

        the index of the attribute

      - ##### m_Name

            String m_Name

        the name of the attribute

  - ### Class weka.filters.unsupervised.attribute.AddNoise

    class AddNoise extends Filter implements Serializable
    serialVersionUID:
      -8499673222857299082L

    - #### Serialized Fields

      - ##### m_AttIndex

            SingleIndex m_AttIndex

        The attribute's index setting.

      - ##### m_Percent

            int m_Percent

        The subsample size, percent of original set, default 10%

      - ##### m_RandomSeed

            int m_RandomSeed

        The random number generator seed

      - ##### m_UseMissing

            boolean m_UseMissing

        Flag if missing values are taken as value.

  - ### Class weka.filters.unsupervised.attribute.AddUserFields

    class AddUserFields extends Filter implements Serializable
    serialVersionUID:
      -2761427344847891585L

    - #### Serialized Fields

      - ##### m_attributeSpecs

            List<AddUserFields.AttributeSpec> m_attributeSpecs

        The new attributes to create

  - ### Class weka.filters.unsupervised.attribute.AddUserFields.AttributeSpec

    class AttributeSpec extends Object implements Serializable
    serialVersionUID:
      -617328946241474608L

    - #### Serialized Fields

      - ##### m_dateFormat

            SimpleDateFormat m_dateFormat

        The date format to use (if the new attribute is a date)

      - ##### m_name

            String m_name

        The name of the new attribute

      - ##### m_nameS

            String m_nameS

        The name after resolving any environment variables

      - ##### m_parsedDate

            Date m_parsedDate

        Holds the parsed date value

      - ##### m_type

            String m_type

        The type of the new attribute

      - ##### m_typeS

            String m_typeS

        The type after resolving any environment variables

      - ##### m_value

            String m_value

        The constant value it should assume

      - ##### m_valueS

            String m_valueS

        The value after resolving any environment variables

  - ### Class weka.filters.unsupervised.attribute.AddValues

    class AddValues extends Filter implements Serializable
    serialVersionUID:
      -8100622241742393656L

    - #### Serialized Fields

      - ##### m_AttIndex

            SingleIndex m_AttIndex

        The attribute's index setting.

      - ##### m_Labels

            ArrayList<String> m_Labels

        The values to add.

      - ##### m_Sort

            boolean m_Sort

        Whether to sort the values.

      - ##### m_SortedIndices

            int[] m_SortedIndices

        the array with the sorted label indices

  - ### Class weka.filters.unsupervised.attribute.CartesianProduct

    class CartesianProduct extends SimpleBatchFilter implements Serializable
    serialVersionUID:
      -227979753639722020L

    - #### Serialized Fields

      - ##### m_Attributes

            Range m_Attributes

        the attribute range to work on

  - ### Class weka.filters.unsupervised.attribute.Center

    class Center extends PotentialClassIgnorer implements Serializable
    serialVersionUID:
      -9101338448900581023L

    - #### Serialized Fields

      - ##### m_Means

            double[] m_Means

        The means

  - ### Class weka.filters.unsupervised.attribute.ChangeDateFormat

    class ChangeDateFormat extends Filter implements Serializable
    serialVersionUID:
      -1609344074013448737L

    - #### Serialized Fields

      - ##### m_AttIndex

            SingleIndex m_AttIndex

        The attribute's index setting.

      - ##### m_DateFormat

            SimpleDateFormat m_DateFormat

        The output date format.

      - ##### m_OutputAttribute

            Attribute m_OutputAttribute

        The output attribute.

  - ### Class weka.filters.unsupervised.attribute.ClassAssigner

    class ClassAssigner extends SimpleStreamFilter implements Serializable
    serialVersionUID:
      1775780193887394115L

    - #### Serialized Fields

      - ##### m_ClassIndex

            int m_ClassIndex

        the class index.

  - ### Class weka.filters.unsupervised.attribute.ClusterMembership

    class ClusterMembership extends Filter implements Serializable
    serialVersionUID:
      6675702504667714026L

    - #### Serialized Fields

      - ##### m_clusterer

            DensityBasedClusterer m_clusterer

        The clusterer

      - ##### m_clusterers

            DensityBasedClusterer[] m_clusterers

        Array for storing the clusterers

      - ##### m_ignoreAttributesRange

            Range m_ignoreAttributesRange

        Range of attributes to ignore

      - ##### m_priors

            double[] m_priors

        The prior probability for each class

      - ##### m_removeAttributes

            Filter m_removeAttributes

        Filter for removing attributes

  - ### Class weka.filters.unsupervised.attribute.Copy

    class Copy extends Filter implements Serializable
    serialVersionUID:
      -8543707493627441566L

    - #### Serialized Fields

      - ##### m_CopyCols

            Range m_CopyCols

        Stores which columns to copy

      - ##### m_SelectedAttributes

            int[] m_SelectedAttributes

        Stores the indexes of the selected attributes in order, once the dataset is seen

  - ### Class weka.filters.unsupervised.attribute.DateToNumeric

    class DateToNumeric extends SimpleBatchFilter implements Serializable
    serialVersionUID:
      -6614650822291796239L

    - #### Serialized Fields

      - ##### m_Cols

            Range m_Cols

        Stores which columns to turn into numeric attributes

      - ##### m_DefaultCols

            String m_DefaultCols

        The default columns to turn into numeric attributes

  - ### Class weka.filters.unsupervised.attribute.Discretize

    class Discretize extends PotentialClassIgnorer implements Serializable
    serialVersionUID:
      -1358531742174527279L

    - #### Serialized Fields

      - ##### m_BinRangePrecision

            int m_BinRangePrecision

        Precision for bin range labels

      - ##### m_CutPoints

            double[][] m_CutPoints

        Store the current cutpoints

      - ##### m_DefaultCols

            String m_DefaultCols

        The default columns to discretize

      - ##### m_DesiredWeightOfInstancesPerInterval

            double m_DesiredWeightOfInstancesPerInterval

        The desired weight of instances per bin

      - ##### m_DiscretizeCols

            Range m_DiscretizeCols

        Stores which columns to Discretize

      - ##### m_FindNumBins

            boolean m_FindNumBins

        Find the number of bins using cross-validated entropy.

      - ##### m_MakeBinary

            boolean m_MakeBinary

        Output binary attributes for discretized attributes.

      - ##### m_NumBins

            int m_NumBins

        The number of bins to divide the attribute into

      - ##### m_SpreadAttributeWeight

            boolean m_SpreadAttributeWeight

        Whether to spread attribute weight when creating binary attributes

      - ##### m_UseBinNumbers

            boolean m_UseBinNumbers

        Use bin numbers rather than ranges for discretized attributes.

      - ##### m_UseEqualFrequency

            boolean m_UseEqualFrequency

        Use equal-frequency binning if unsupervised discretization turned on

  - ### Class weka.filters.unsupervised.attribute.FirstOrder

    class FirstOrder extends Filter implements Serializable
    serialVersionUID:
      -7500464545400454179L

    - #### Serialized Fields

      - ##### m_DeltaCols

            Range m_DeltaCols

        Stores which columns to take differences between

  - ### Class weka.filters.unsupervised.attribute.FixedDictionaryStringToWordVector

    class FixedDictionaryStringToWordVector extends SimpleStreamFilter implements Serializable
    serialVersionUID:
      7990892846966916757L

    - #### Serialized Fields

      - ##### m_dictionaryFile

            File m_dictionaryFile

      - ##### m_dictionaryIsBinary

            boolean m_dictionaryIsBinary

        Whether the dictionary file contains a binary serialized dictionary, rather than plain text - used when loading from a file in order to differentiate

      - ##### m_vectorizer

            DictionaryBuilder m_vectorizer

  - ### Class weka.filters.unsupervised.attribute.InterquartileRange

    class InterquartileRange extends SimpleBatchFilter implements Serializable
    serialVersionUID:
      -227879653639723030L

    - #### Serialized Fields

      - ##### m_AttributeIndices

            int[] m_AttributeIndices

        the generated indices (only for performance reasons)

      - ##### m_Attributes

            Range m_Attributes

        the attribute range to work on

      - ##### m_DetectionPerAttribute

            boolean m_DetectionPerAttribute

        whether to generate Outlier/ExtremeValue attributes for each attribute instead of a general one

      - ##### m_ExtremeValuesAsOutliers

            boolean m_ExtremeValuesAsOutliers

        whether extreme values are also tagged as outliers

      - ##### m_ExtremeValuesFactor

            double m_ExtremeValuesFactor

        the factor for detecting extreme values, by default 2*m_OutlierFactor

      - ##### m_IQR

            double[] m_IQR

        the interquartile range

      - ##### m_LowerExtremeValue

            double[] m_LowerExtremeValue

        the lower extreme value threshold (= Q1 - EVF*IQR)

      - ##### m_LowerOutlier

            double[] m_LowerOutlier

        the lower outlier threshold (= Q1 - OF*IQR)

      - ##### m_Median

            double[] m_Median

        the median

      - ##### m_OutlierAttributePosition

            int[] m_OutlierAttributePosition

        the position of the outlier attribute

      - ##### m_OutlierFactor

            double m_OutlierFactor

        the factor for detecting outliers

      - ##### m_OutputOffsetMultiplier

            boolean m_OutputOffsetMultiplier

        whether to add another attribute called "Offset", that lists the 'multiplier' by which the outlier/extreme value is away from the median, i.e., value = median + 'multiplier' * IQR
        automatically enables m_DetectionPerAttribute!

      - ##### m_UpperExtremeValue

            double[] m_UpperExtremeValue

        the upper extreme value threshold (= Q3 + EVF*IQR)

      - ##### m_UpperOutlier

            double[] m_UpperOutlier

        the upper outlier threshold (= Q3 + OF*IQR)

  - ### Class weka.filters.unsupervised.attribute.KernelFilter

    class KernelFilter extends SimpleBatchFilter implements Serializable
    serialVersionUID:
      213800899640387499L

    - #### Serialized Fields

      - ##### m_ActualFilter

            Filter m_ActualFilter

        for centering/standardizing the data (the actual filter to use)

      - ##### m_ActualKernel

            Kernel m_ActualKernel

        the Kernel which is actually used for computation

      - ##### m_checksTurnedOff

            boolean m_checksTurnedOff

        Turn off all checks and conversions? Turning them off assumes that data is purely numeric, doesn't contain any missing values, and has a nominal class. Turning them off also means that no header information will be stored if the machine is linear. Finally, it also assumes that no instance has a weight equal to 0.

      - ##### m_Filter

            Filter m_Filter

        for centering/standardizing the data

      - ##### m_InitFile

            File m_InitFile

        The dataset to initialize the filter with

      - ##### m_InitFileClassIndex

            SingleIndex m_InitFileClassIndex

        the class index for the file to initialized with
        See Also:
          - `KernelFilter.m_InitFile`

      - ##### m_Initialized

            boolean m_Initialized

        whether the filter was initialized

      - ##### m_Kernel

            Kernel m_Kernel

        Kernel to use

      - ##### m_KernelFactor

            double m_KernelFactor

        the calculated kernel factor
        See Also:
          - `KernelFilter.m_KernelFactorExpression`

      - ##### m_KernelFactorExpression

            String m_KernelFactorExpression

        optimizes the kernel with this formula (A = # of attributes, N = # of instances)

      - ##### m_Missing

            ReplaceMissingValues m_Missing

        The filter used to get rid of missing values.

      - ##### m_NominalToBinary

            NominalToBinary m_NominalToBinary

        The filter used to make attributes numeric.

      - ##### m_NumTrainInstances

            int m_NumTrainInstances

        The number of instances in the training data.

  - ### Class weka.filters.unsupervised.attribute.MakeIndicator

    class MakeIndicator extends Filter implements Serializable
    serialVersionUID:
      766001176862773163L

    - #### Serialized Fields

      - ##### m_AttIndex

            SingleIndex m_AttIndex

        The attribute's index setting.

      - ##### m_Numeric

            boolean m_Numeric

        Make Boolean attribute numeric.

      - ##### m_ValIndex

            Range m_ValIndex

        The value's index

  - ### Class weka.filters.unsupervised.attribute.MathExpression

    class MathExpression extends PotentialClassIgnorer implements Serializable
    serialVersionUID:
      -3713222714671997901L

    - #### Serialized Fields

      - ##### m_attStats

            Stats[] m_attStats

        Attributes statistics

      - ##### m_CompiledExpression

            Primitives.DoubleExpression m_CompiledExpression

        The compiled modification expression

      - ##### m_CurrentValue

            SimpleVariableDeclarations.VariableInitializer m_CurrentValue

        VariableInitializer for the current value 'A' in an expression

      - ##### m_expression

            String m_expression

        The modification expression

      - ##### m_InstancesHelper

            InstancesHelper m_InstancesHelper

        InstancesHelpers for different indices

      - ##### m_SelectCols

            Range m_SelectCols

        Stores which columns to select as a funky range

      - ##### m_StatsHelper

            StatsHelper m_StatsHelper

        StatsHelpers for different indices

  - ### Class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues

    class MergeInfrequentNominalValues extends SimpleBatchFilter implements Serializable
    serialVersionUID:
      4444337331921333847L

    - #### Serialized Fields

      - ##### m_AttToBeModified

            boolean[] m_AttToBeModified

        Indicators for which attributes need to be changed.

      - ##### m_MinimumFrequency

            int m_MinimumFrequency

        Set the minimum frequency for a value not to be merged.

      - ##### m_NewValues

            int[][] m_NewValues

        The new values.

      - ##### m_SelectCols

            Range m_SelectCols

        Stores which atributes to operate on (or nto)

      - ##### m_SelectedAttributes

            int[] m_SelectedAttributes

        Stores the indexes of the selected attributes in order.

      - ##### m_UseShortIDs

            boolean m_UseShortIDs

        Whether to use short identifiers for merge values.

  - ### Class weka.filters.unsupervised.attribute.MergeManyValues

    class MergeManyValues extends PotentialClassIgnorer implements Serializable
    serialVersionUID:
      4649332102154713625L

    - #### Serialized Fields

      - ##### m_AttIndex

            SingleIndex m_AttIndex

        The attribute's index setting.

      - ##### m_Label

            String m_Label

        The first value's index setting.

      - ##### m_MergeRange

            Range m_MergeRange

        The merge value's index setting.

  - ### Class weka.filters.unsupervised.attribute.MergeTwoValues

    class MergeTwoValues extends Filter implements Serializable
    serialVersionUID:
      2925048980504034018L

    - #### Serialized Fields

      - ##### m_AttIndex

            SingleIndex m_AttIndex

        The attribute's index setting.

      - ##### m_FirstIndex

            SingleIndex m_FirstIndex

        The first value's index setting.

      - ##### m_SecondIndex

            SingleIndex m_SecondIndex

        The second value's index setting.

  - ### Class weka.filters.unsupervised.attribute.NominalToBinary

    class NominalToBinary extends Filter implements Serializable
    serialVersionUID:
      -1130642825710549138L

    - #### Serialized Fields

      - ##### m_Columns

            Range m_Columns

        Stores which columns to act on

      - ##### m_needToTransform

            boolean m_needToTransform

        Whether we need to transform at all

      - ##### m_Numeric

            boolean m_Numeric

        Are the new attributes going to be nominal or numeric ones?

      - ##### m_SpreadAttributeWeight

            boolean m_SpreadAttributeWeight

        Whether to spread attribute weight when creating binary attributes

      - ##### m_TransformAll

            boolean m_TransformAll

        Are all values transformed into new attributes?

  - ### Class weka.filters.unsupervised.attribute.NominalToString

    class NominalToString extends Filter implements Serializable
    serialVersionUID:
      8655492378380068939L

    - #### Serialized Fields

      - ##### m_AttIndex

            Range m_AttIndex

        The attribute's index setting.

  - ### Class weka.filters.unsupervised.attribute.Normalize

    class Normalize extends PotentialClassIgnorer implements Serializable
    serialVersionUID:
      -8158531150984362898L

    - #### Serialized Fields

      - ##### m_MaxArray

            double[] m_MaxArray

        The maximum values for numeric attributes.

      - ##### m_MinArray

            double[] m_MinArray

        The minimum values for numeric attributes.

      - ##### m_Scale

            double m_Scale

        The scaling factor of the output range.

      - ##### m_Translation

            double m_Translation

        The translation of the output range.

  - ### Class weka.filters.unsupervised.attribute.NumericCleaner

    class NumericCleaner extends SimpleStreamFilter implements Serializable
    serialVersionUID:
      -352890679895066592L

    - #### Serialized Fields

      - ##### m_CloseTo

            double m_CloseTo

        the number the values are checked for closeness to

      - ##### m_CloseToDefault

            double m_CloseToDefault

        the default replacement value for numbers "close-to"

      - ##### m_CloseToTolerance

            double m_CloseToTolerance

        the tolerance distance, below which numbers are considered being "close-to"

      - ##### m_Cols

            Range m_Cols

        Stores which columns to cleanse

      - ##### m_Decimals

            int m_Decimals

        the number of decimals to round to (-1 means no rounding)

      - ##### m_IncludeClass

            boolean m_IncludeClass

        whether to include the class attribute

      - ##### m_MaxDefault

            double m_MaxDefault

        the maximum default replacement value

      - ##### m_MaxThreshold

            double m_MaxThreshold

        the maximum threshold

      - ##### m_MinDefault

            double m_MinDefault

        the minimum default replacement value

      - ##### m_MinThreshold

            double m_MinThreshold

        the minimum threshold

  - ### Class weka.filters.unsupervised.attribute.NumericToBinary

    class NumericToBinary extends PotentialClassIgnorer implements Serializable
    serialVersionUID:
      2616879323359470802L

    - #### Serialized Fields

      - ##### m_Cols

            Range m_Cols

        Stores which columns to turn into binary

      - ##### m_DefaultCols

            String m_DefaultCols

        The default columns to turn into binary

  - ### Class weka.filters.unsupervised.attribute.NumericToDate

    class NumericToDate extends SimpleBatchFilter implements Serializable
    serialVersionUID:
      -6514657821295776239L

    - #### Serialized Fields

      - ##### m_Cols

            Range m_Cols

        Stores which columns to turn into date attributes

      - ##### m_DateFormat

            SimpleDateFormat m_DateFormat

        The output date format.

      - ##### m_DefaultCols

            String m_DefaultCols

        The default columns to turn into date attributes

  - ### Class weka.filters.unsupervised.attribute.NumericToNominal

    class NumericToNominal extends SimpleBatchFilter implements Serializable
    serialVersionUID:
      -6614630932899796239L

    - #### Serialized Fields

      - ##### m_Cols

            Range m_Cols

        Stores which columns to turn into nominals

      - ##### m_DefaultCols

            String m_DefaultCols

        The default columns to turn into nominals

  - ### Class weka.filters.unsupervised.attribute.NumericTransform

    class NumericTransform extends Filter implements Serializable
    serialVersionUID:
      -8561413333351366934L

    - #### Serialized Fields

      - ##### m_Class

            String m_Class

        Class containing transformation method.

      - ##### m_Cols

            Range m_Cols

        Stores which columns to transform.

      - ##### m_Method

            String m_Method

        Transformation method.

  - ### Class weka.filters.unsupervised.attribute.Obfuscate

    class Obfuscate extends Filter implements Serializable
    serialVersionUID:
      -343922772462971561L

  - ### Class weka.filters.unsupervised.attribute.OrdinalToNumeric

    class OrdinalToNumeric extends PotentialClassIgnorer implements Serializable
    serialVersionUID:
      -5199516576940135696L

    - #### Serialized Fields

      - ##### m_range

            String m_range

        Textual range string

      - ##### m_resolvedRange

            String m_resolvedRange

        Holds the resolved range

      - ##### m_selectedRange

            Range m_selectedRange

        Range of columns to consider

  - ### Class weka.filters.unsupervised.attribute.PartitionedMultiFilter

    class PartitionedMultiFilter extends SimpleBatchFilter implements Serializable
    serialVersionUID:
      -6293720886005713120L

    - #### Serialized Fields

      - ##### m_Filters

            Filter[] m_Filters

        The filters.

      - ##### m_IndicesUnused

            int[] m_IndicesUnused

        the indices of the unused attributes.

      - ##### m_Ranges

            Range[] m_Ranges

        The attribute ranges.

      - ##### m_RemoveUnused

            boolean m_RemoveUnused

        Whether unused attributes are left out of the output.

  - ### Class weka.filters.unsupervised.attribute.PKIDiscretize

    class PKIDiscretize extends Discretize implements Serializable
    serialVersionUID:
      6153101248977702675L

  - ### Class weka.filters.unsupervised.attribute.PotentialClassIgnorer

    class PotentialClassIgnorer extends Filter implements Serializable
    serialVersionUID:
      8625371119276845454L

    - #### Serialized Fields

      - ##### m_ClassIndex

            int m_ClassIndex

        Storing the class index

      - ##### m_IgnoreClass

            boolean m_IgnoreClass

        True if the class is to be unset

  - ### Class weka.filters.unsupervised.attribute.PrincipalComponents

    class PrincipalComponents extends Filter implements Serializable
    serialVersionUID:
      -5649876869480249303L

    - #### Serialized Fields

      - ##### m_AttributeFilter

            Remove m_AttributeFilter

        Filter for removing class attribute, nominal attributes with 0 or 1 value.

      - ##### m_center

            boolean m_center

        If true, center (rather than standardize) the data and compute PCA from covariance (rather than correlation) matrix.

      - ##### m_centerFilter

            Center m_centerFilter

        Filter for centering the data

      - ##### m_ClassIndex

            int m_ClassIndex

        Class index.

      - ##### m_Correlation

            no.uib.cipr.matrix.UpperSymmDenseMatrix m_Correlation

        Correlation matrix for the original data.

      - ##### m_CoverVariance

            double m_CoverVariance

        the amount of varaince to cover in the original data when retaining the best n PC's.

      - ##### m_Eigenvalues

            double[] m_Eigenvalues

        Eigenvalues for the corresponding eigenvectors.

      - ##### m_Eigenvectors

            double[][] m_Eigenvectors

        Will hold the unordered linear transformations of the (normalized) original data.

      - ##### m_HasClass

            boolean m_HasClass

        Data has a class set.

      - ##### m_MaxAttributes

            int m_MaxAttributes

        maximum number of attributes in the transformed data (-1 for all).

      - ##### m_MaxAttrsInName

            int m_MaxAttrsInName

        maximum number of attributes in the transformed attribute name.

      - ##### m_NominalToBinaryFilter

            NominalToBinary m_NominalToBinaryFilter

        Filter for turning nominal values into numeric ones.

      - ##### m_NumAttribs

            int m_NumAttribs

        Number of attributes.

      - ##### m_NumInstances

            int m_NumInstances

        Number of instances.

      - ##### m_OutputNumAtts

            int m_OutputNumAtts

        The number of attributes in the pc transformed data.

      - ##### m_ReplaceMissingFilter

            ReplaceMissingValues m_ReplaceMissingFilter

        Filters for replacing missing values.

      - ##### m_SortedEigens

            int[] m_SortedEigens

        Sorted eigenvalues.

      - ##### m_standardizeFilter

            Standardize m_standardizeFilter

        Filter for standardizing the data

      - ##### m_SumOfEigenValues

            double m_SumOfEigenValues

        sum of the eigenvalues.

      - ##### m_TrainCopy

            Instances m_TrainCopy

        Keep a copy for the class attribute (if set).

      - ##### m_TrainInstances

            Instances m_TrainInstances

        The data to transform analyse/transform.

      - ##### m_TransformedFormat

            Instances m_TransformedFormat

        The header for the transformed data format.

  - ### Class weka.filters.unsupervised.attribute.RandomProjection

    class RandomProjection extends Filter implements Serializable
    serialVersionUID:
      4428905532728645880L

    - #### Serialized Fields

      - ##### m_distribution

            int m_distribution

        Stores the distribution to use for calculating the random matrix

      - ##### m_k

            int m_k

        Stores the number of dimensions to reduce the data to

      - ##### m_ntob

            Filter m_ntob

        The NominalToBinary filter applied to the data before this filter

      - ##### m_OutputFormatDefined

            boolean m_OutputFormatDefined

        Keeps track of output format if it is defined or not

      - ##### m_percent

            double m_percent

        Stores the dimensionality the data should be reduced to as percentage of the original dimension

      - ##### m_random

            Random m_random

        The random number generator used for generating the random matrix

      - ##### m_replaceMissing

            Filter m_replaceMissing

        The ReplaceMissingValues filter

      - ##### m_rmatrix

            double[][] m_rmatrix

        The random matrix

      - ##### m_rndmSeed

            int m_rndmSeed

        Stores the random seed used to generate the random matrix

      - ##### m_useReplaceMissing

            boolean m_useReplaceMissing

        Should the missing values be replaced using unsupervised.ReplaceMissingValues filter

  - ### Class weka.filters.unsupervised.attribute.RandomSubset

    class RandomSubset extends SimpleBatchFilter implements Serializable
    serialVersionUID:
      2911221724251628050L

    - #### Serialized Fields

      - ##### m_Indices

            int[] m_Indices

        The indices of the attributes that got selected.

      - ##### m_invertSelection

            boolean m_invertSelection

        Whether to randomly remove rather than select

      - ##### m_NumAttributes

            double m_NumAttributes

        The number of attributes to randomly choose (>= 1 absolute number of attributes, < 1 percentage).

      - ##### m_Seed

            int m_Seed

        The seed value.

  - ### Class weka.filters.unsupervised.attribute.Remove

    class Remove extends Filter implements Serializable
    serialVersionUID:
      5011337331921522847L

    - #### Serialized Fields

      - ##### m_SelectCols

            Range m_SelectCols

        Stores which columns to select as a funky range

      - ##### m_SelectedAttributes

            int[] m_SelectedAttributes

        Stores the indexes of the selected attributes in order, once the dataset is seen

  - ### Class weka.filters.unsupervised.attribute.RemoveByName

    class RemoveByName extends SimpleStreamFilter implements Serializable
    serialVersionUID:
      -3335106965521265631L

    - #### Serialized Fields

      - ##### m_Expression

            String m_Expression

        the regular expression for selecting the attributes by name.

      - ##### m_InvertSelection

            boolean m_InvertSelection

        whether to invert the matching sense.

      - ##### m_Remove

            Remove m_Remove

        the Remove filter used internally for removing the attributes.

  - ### Class weka.filters.unsupervised.attribute.RemoveType

    class RemoveType extends Filter implements Serializable
    serialVersionUID:
      -3563999462782486279L

    - #### Serialized Fields

      - ##### m_attributeFilter

            Remove m_attributeFilter

        The attribute filter used to do the filtering

      - ##### m_attTypeToDelete

            int m_attTypeToDelete

        The type of attribute to delete

      - ##### m_invert

            boolean m_invert

        Whether to invert selection

  - ### Class weka.filters.unsupervised.attribute.RemoveUseless

    class RemoveUseless extends Filter implements Serializable
    serialVersionUID:
      -8659417851407640038L

    - #### Serialized Fields

      - ##### m_maxVariancePercentage

            double m_maxVariancePercentage

        The type of attribute to delete

      - ##### m_removeFilter

            Remove m_removeFilter

        The filter used to remove attributes

  - ### Class weka.filters.unsupervised.attribute.RenameAttribute

    class RenameAttribute extends SimpleStreamFilter implements Serializable
    serialVersionUID:
      4216491776378279596L

    - #### Serialized Fields

      - ##### m_AttributeIndices

            Range m_AttributeIndices

        the attribute range to work on.

      - ##### m_Find

            String m_Find

        the regular expression that the attribute names have to match.

      - ##### m_Replace

            String m_Replace

        the regular expression to replace the attribute name with.

      - ##### m_ReplaceAll

            boolean m_ReplaceAll

        whether to replace all occurrences or just the first.

  - ### Class weka.filters.unsupervised.attribute.RenameNominalValues

    class RenameNominalValues extends Filter implements Serializable
    serialVersionUID:
      -2121767582746512209L

    - #### Serialized Fields

      - ##### m_ignoreCase

            boolean m_ignoreCase

        True if case is to be ignored when matching nominal values

      - ##### m_invert

            boolean m_invert

        True if the matching sense (for attributes) is to be inverted

      - ##### m_renameMap

            Map<String,String> m_renameMap

        The map of nominal values and their replacements

      - ##### m_renameVals

            String m_renameVals

        The comma-separated list of nominal values and their replacements

      - ##### m_selectedAttributes

            int[] m_selectedAttributes

        Stores the indexes of the selected attributes in order, once the dataset is seen

      - ##### m_selectedCols

            Range m_selectedCols

        The range object to use if a range has been supplied

      - ##### m_selectedColsString

            String m_selectedColsString

        Range specification or comma-separated list of attribute names

  - ### Class weka.filters.unsupervised.attribute.Reorder

    class Reorder extends Filter implements Serializable
    serialVersionUID:
      -1135571321097202292L

    - #### Serialized Fields

      - ##### m_InputStringIndex

            int[] m_InputStringIndex

        Contains an index of string attributes in the input format that survive the filtering process -- some entries may be duplicated

      - ##### m_NewOrderCols

            String m_NewOrderCols

        Stores which columns to reorder

      - ##### m_SelectedAttributes

            int[] m_SelectedAttributes

        Stores the indexes of the selected attributes in order, once the dataset is seen

      - ##### m_setAllAttributeWeightsToOne

            boolean m_setAllAttributeWeightsToOne

        Whether to set all attribute weights to 1.0 in the reordered data.

  - ### Class weka.filters.unsupervised.attribute.ReplaceMissingValues

    class ReplaceMissingValues extends PotentialClassIgnorer implements Serializable
    serialVersionUID:
      8349568310991609867L

    - #### Serialized Fields

      - ##### m_ModesAndMeans

            double[] m_ModesAndMeans

        The modes and means

  - ### Class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant

    class ReplaceMissingWithUserConstant extends PotentialClassIgnorer implements Serializable
    serialVersionUID:
      -7334039452189350356L

    - #### Serialized Fields

      - ##### m_dateConstant

            String m_dateConstant

        Constant for replacing missing values in date attributes with

      - ##### m_dateConstVal

            double m_dateConstVal

        Parsed date value as a double

      - ##### m_defaultDateFormat

            String m_defaultDateFormat

        Formatting string to use for parsing the date constant

      - ##### m_nominalStringConstant

            String m_nominalStringConstant

        Constant for replacing missing values in nominal/string atts with

      - ##### m_numericConstant

            String m_numericConstant

        Constant for replacing missing values in numeric attributes with

      - ##### m_numericConstVal

            double m_numericConstVal

        Parsed numeric constant value

      - ##### m_range

            String m_range

      - ##### m_resolvedDateConstant

            String m_resolvedDateConstant

        Replacement value for date atts after resolving environment vars

      - ##### m_resolvedDateFormat

            String m_resolvedDateFormat

        Formatting string after resolving environment vars

      - ##### m_resolvedNominalStringConstant

            String m_resolvedNominalStringConstant

        Replacement value for nominal/string atts after resolving environment vars

      - ##### m_resolvedNumericConstant

            String m_resolvedNumericConstant

        Replacement value for numeric atts after resolving environment vars

      - ##### m_resolvedRange

            String m_resolvedRange

      - ##### m_selectedRange

            Range m_selectedRange

        Range of columns to consider

  - ### Class weka.filters.unsupervised.attribute.ReplaceWithMissingValue

    class ReplaceWithMissingValue extends SimpleBatchFilter implements Serializable
    serialVersionUID:
      -2356630932899796239L

    - #### Serialized Fields

      - ##### m_Cols

            Range m_Cols

        Stores which columns to turn into nominals

      - ##### m_DefaultCols

            String m_DefaultCols

        The default columns to turn into nominals

      - ##### m_IgnoreClass

            boolean m_IgnoreClass

        True if the class is to be unset

      - ##### m_Probability

            double m_Probability

        The probability

      - ##### m_Seed

            int m_Seed

        The seed for the random number generator

  - ### Class weka.filters.unsupervised.attribute.SortLabels

    class SortLabels extends SimpleStreamFilter implements Serializable
    serialVersionUID:
      7815204879694105691L

    - #### Serialized Fields

      - ##### m_AttributeIndices

            Range m_AttributeIndices

        the range of attributes to process (only relational ones will be processed).

      - ##### m_Comparator

            Comparator<String> m_Comparator

        the comparator to use for sorting.

      - ##### m_NewOrder

            int[][] m_NewOrder

        the new order for the labels.

      - ##### m_SortType

            int m_SortType

        the sort type.

  - ### Class weka.filters.unsupervised.attribute.SortLabels.CaseInsensitiveComparator

    class CaseInsensitiveComparator extends Object implements Serializable
    serialVersionUID:
      -4515292733342486066L

  - ### Class weka.filters.unsupervised.attribute.SortLabels.CaseSensitiveComparator

    class CaseSensitiveComparator extends Object implements Serializable
    serialVersionUID:
      7071450356783873277L

  - ### Class weka.filters.unsupervised.attribute.Standardize

    class Standardize extends PotentialClassIgnorer implements Serializable
    serialVersionUID:
      -6830769026855053281L

    - #### Serialized Fields

      - ##### m_Means

            double[] m_Means

        The means

      - ##### m_StdDevs

            double[] m_StdDevs

        The variances

  - ### Class weka.filters.unsupervised.attribute.StringToNominal

    class StringToNominal extends Filter implements Serializable
    serialVersionUID:
      4864084427902797605L

    - #### Serialized Fields

      - ##### m_AttIndices

            Range m_AttIndices

        The attribute's range indices setting.

  - ### Class weka.filters.unsupervised.attribute.StringToWordVector

    class StringToWordVector extends Filter implements Serializable
    serialVersionUID:
      8249106275278565424L

    - #### Serialized Fields

      - ##### m_dictionaryBuilder

            DictionaryBuilder m_dictionaryBuilder

        Used to build and manage the dictionary + vectorization

      - ##### m_dictionaryFile

            File m_dictionaryFile

        File to save the dictionary to

      - ##### m_dictionaryIsBinary

            boolean m_dictionaryIsBinary

        Whether to save the dictionary in serialized form rather than as plain text

      - ##### m_filterType

            int m_filterType

        The normalization to apply.

      - ##### m_PeriodicPruningRate

            double m_PeriodicPruningRate

        The percentage at which to periodically prune the dictionary.

  - ### Class weka.filters.unsupervised.attribute.SwapValues

    class SwapValues extends Filter implements Serializable
    serialVersionUID:
      6155834679414275855L

    - #### Serialized Fields

      - ##### m_AttIndex

            SingleIndex m_AttIndex

        The attribute's index setting.

      - ##### m_FirstIndex

            SingleIndex m_FirstIndex

        The first value's index setting.

      - ##### m_SecondIndex

            SingleIndex m_SecondIndex

        The second value's index setting.

  - ### Class weka.filters.unsupervised.attribute.TimeSeriesDelta

    class TimeSeriesDelta extends TimeSeriesTranslate implements Serializable
    serialVersionUID:
      3101490081896634942L

  - ### Class weka.filters.unsupervised.attribute.TimeSeriesTranslate

    class TimeSeriesTranslate extends AbstractTimeSeries implements Serializable
    serialVersionUID:
      -8901621509691785705L

  - ### Class weka.filters.unsupervised.attribute.Transpose

    class Transpose extends SimpleBatchFilter implements Serializable
    serialVersionUID:
      213999899640387499L

- ## Package weka.filters.unsupervised.instance

  - ### Class weka.filters.unsupervised.instance.NonSparseToSparse

    class NonSparseToSparse extends Filter implements Serializable
    serialVersionUID:
      4694489111366063852L

    - #### Serialized Fields

      - ##### m_encodeMissingAsZero

            boolean m_encodeMissingAsZero

  - ### Class weka.filters.unsupervised.instance.Randomize

    class Randomize extends Filter implements Serializable
    serialVersionUID:
      8854479785121877582L

    - #### Serialized Fields

      - ##### m_Random

            Random m_Random

        The current random number generator

      - ##### m_Seed

            int m_Seed

        The random number seed

  - ### Class weka.filters.unsupervised.instance.RemoveDuplicates

    class RemoveDuplicates extends SimpleBatchFilter implements Serializable
    serialVersionUID:
      4518686110979589602L

  - ### Class weka.filters.unsupervised.instance.RemoveFolds

    class RemoveFolds extends Filter implements Serializable
    serialVersionUID:
      8220373305559055700L

    - #### Serialized Fields

      - ##### m_Fold

            int m_Fold

        Fold to output

      - ##### m_Inverse

            boolean m_Inverse

        Indicates if inverse of selection is to be output.

      - ##### m_NumFolds

            int m_NumFolds

        Number of folds to split dataset into

      - ##### m_Seed

            long m_Seed

        Random number seed.

  - ### Class weka.filters.unsupervised.instance.RemoveFrequentValues

    class RemoveFrequentValues extends Filter implements Serializable
    serialVersionUID:
      -2447432930070059511L

    - #### Serialized Fields

      - ##### m_AttIndex

            SingleIndex m_AttIndex

        The attribute's index setting.

      - ##### m_Invert

            boolean m_Invert

        whether to invert the matching sense.

      - ##### m_LeastValues

            boolean m_LeastValues

        whether to retain values with least instances instead of most.

      - ##### m_ModifyHeader

            boolean m_ModifyHeader

        Modify header for nominal attributes?

      - ##### m_NominalMapping

            int[] m_NominalMapping

        If m_ModifyHeader, stores a mapping from old to new indexes

      - ##### m_NumValues

            int m_NumValues

        the number of values to retain.

      - ##### m_Values

            HashSet<String> m_Values

        contains the values to retain

  - ### Class weka.filters.unsupervised.instance.RemoveMisclassified

    class RemoveMisclassified extends Filter implements Serializable
    serialVersionUID:
      5469157004717663171L

    - #### Serialized Fields

      - ##### m_classIndex

            int m_classIndex

        The attribute to treat as the class for purposes of cleansing.

      - ##### m_cleansingClassifier

            Classifier m_cleansingClassifier

        The classifier used to do the cleansing

      - ##### m_firstBatchFinished

            boolean m_firstBatchFinished

        Have we processed the first batch (i.e. training data)?

      - ##### m_invertMatching

            boolean m_invertMatching

        Whether to invert the match so the correctly classified instances are discarded

      - ##### m_numericClassifyThreshold

            double m_numericClassifyThreshold

        The threshold for deciding when a numeric value is correctly classified

      - ##### m_numOfCleansingIterations

            int m_numOfCleansingIterations

        The maximum number of cleansing iterations to perform (<1 = until fully cleansed)

      - ##### m_numOfCrossValidationFolds

            int m_numOfCrossValidationFolds

        The number of cross validation folds to perform (<2 = no cross validation)

  - ### Class weka.filters.unsupervised.instance.RemovePercentage

    class RemovePercentage extends Filter implements Serializable
    serialVersionUID:
      2150341191158533133L

    - #### Serialized Fields

      - ##### m_Inverse

            boolean m_Inverse

        Indicates if inverse of selection is to be output.

      - ##### m_Percentage

            double m_Percentage

        Percentage of instances to select.

  - ### Class weka.filters.unsupervised.instance.RemoveRange

    class RemoveRange extends Filter implements Serializable
    serialVersionUID:
      -3064641215340828695L

    - #### Serialized Fields

      - ##### m_Range

            Range m_Range

        Range of instances requested by the user.

  - ### Class weka.filters.unsupervised.instance.RemoveWithValues

    class RemoveWithValues extends Filter implements Serializable
    serialVersionUID:
      4752870193679263361L

    - #### Serialized Fields

      - ##### m_AttIndex

            SingleIndex m_AttIndex

        The attribute's index setting.

      - ##### m_dontFilterAfterFirstBatch

            boolean m_dontFilterAfterFirstBatch

        Whether to filter instances after the first batch has been processed

      - ##### m_MatchMissingValues

            boolean m_MatchMissingValues

        True if missing values should count as a match

      - ##### m_ModifyHeader

            boolean m_ModifyHeader

        Modify header for nominal attributes?

      - ##### m_NominalMapping

            int[] m_NominalMapping

        If m_ModifyHeader, stores a mapping from old to new indexes

      - ##### m_Value

            double m_Value

        Stores which value of a numeric attribute is to be used for filtering.

      - ##### m_Values

            Range m_Values

        Stores which values of nominal attribute are to be used for filtering.

  - ### Class weka.filters.unsupervised.instance.Resample

    class Resample extends Filter implements Serializable
    serialVersionUID:
      3119607037607101160L

    - #### Serialized Fields

      - ##### m_InvertSelection

            boolean m_InvertSelection

        Whether to invert the selection (only if instances are drawn WITHOUT replacement)
        See Also:
          - `Resample.m_NoReplacement`

      - ##### m_NoReplacement

            boolean m_NoReplacement

        Whether to perform sampling with replacement or without

      - ##### m_RandomSeed

            int m_RandomSeed

        The random number generator seed

      - ##### m_SampleSizePercent

            double m_SampleSizePercent

        The subsample size, percent of original set, default 100%

  - ### Class weka.filters.unsupervised.instance.ReservoirSample

    class ReservoirSample extends Filter implements Serializable
    serialVersionUID:
      3119607037607101160L

    - #### Serialized Fields

      - ##### m_containsStringAtts

            boolean m_containsStringAtts

        True if the incoming data contains string attributes

      - ##### m_currentInst

            int m_currentInst

        The current instance being processed

      - ##### m_random

            Random m_random

        The random number generator

      - ##### m_RandomSeed

            int m_RandomSeed

        The random number generator seed

      - ##### m_SampleSize

            int m_SampleSize

        The subsample size, number of instances%

      - ##### m_subSample

            Object[] m_subSample

        Holds the sub-sample (reservoir)

  - ### Class weka.filters.unsupervised.instance.SparseToNonSparse

    class SparseToNonSparse extends Filter implements Serializable
    serialVersionUID:
      2481634184210236074L

  - ### Class weka.filters.unsupervised.instance.SubsetByExpression

    class SubsetByExpression extends SimpleBatchFilter implements Serializable
    serialVersionUID:
      5628686110979589602L

    - #### Serialized Fields

      - ##### m_Expression

            String m_Expression

        the expresion to use for filtering.

      - ##### m_filterAfterFirstBatch

            boolean m_filterAfterFirstBatch

        Whether to filter instances after the first batch has been processed

- ## Package weka.gui

  - ### Class weka.gui.AbstractGUIApplication

    class AbstractGUIApplication extends JPanel implements Serializable
    serialVersionUID:
      -2116770422043462730L

    - #### Serialized Fields

      - ##### m_applicationSettings

            Settings m_applicationSettings

        The settings for the application

      - ##### m_perspectiveManager

            PerspectiveManager m_perspectiveManager

        Manages perspectives and provides the perspectives toolbar

  - ### Class weka.gui.AbstractPerspective

    class AbstractPerspective extends JPanel implements Serializable
    serialVersionUID:
      1919714661641262879L

    - #### Serialized Fields

      - ##### m_isActive

            boolean m_isActive

        True if this perspective is currently the active/visible one

      - ##### m_isLoaded

            boolean m_isLoaded

        True if this perspective has been loaded

      - ##### m_log

            Logger m_log

        Logger for this perspective

      - ##### m_mainApplication

            GUIApplication m_mainApplication

        The main application that is displaying this perspective

      - ##### m_perspectiveIcon

            Icon m_perspectiveIcon

        Icon for this perspective

      - ##### m_perspectiveID

            String m_perspectiveID

        The ID of the perspective

      - ##### m_perspectiveTipText

            String m_perspectiveTipText

        Tip text for this perspective

      - ##### m_perspectiveTitle

            String m_perspectiveTitle

        The title of the perspective

  - ### Class weka.gui.AttributeListPanel

    class AttributeListPanel extends JPanel implements Serializable
    serialVersionUID:
      -2030706987910400362L

    - #### Serialized Fields

      - ##### m_Model

            weka.gui.AttributeListPanel.AttributeTableModel m_Model

        The table model containing attribute names

      - ##### m_Table

            JTable m_Table

        The table displaying attribute names

  - ### Class weka.gui.AttributeSelectionPanel

    class AttributeSelectionPanel extends JPanel implements Serializable
    serialVersionUID:
      627131485290359194L

    - #### Serialized Fields

      - ##### m_IncludeAll

            JButton m_IncludeAll

        Press to select all attributes

      - ##### m_Invert

            JButton m_Invert

        Press to invert the current selection

      - ##### m_Model

            weka.gui.AttributeSelectionPanel.AttributeTableModel m_Model

        The table model containing attribute names and selection status

      - ##### m_Pattern

            JButton m_Pattern

        Press to enter a perl regular expression for selection

      - ##### m_PatternRegEx

            String m_PatternRegEx

        The current regular expression.

      - ##### m_RemoveAll

            JButton m_RemoveAll

        Press to deselect all attributes

      - ##### m_Table

            JTable m_Table

        The table displaying attribute names and selection status

  - ### Class weka.gui.AttributeSummaryPanel

    class AttributeSummaryPanel extends JPanel implements Serializable
    serialVersionUID:
      -5434987925737735880L

    - #### Serialized Fields

      - ##### m_allEqualWeights

            boolean m_allEqualWeights

        Do all instances have the same weight

      - ##### m_AttributeNameLab

            JLabel m_AttributeNameLab

        Displays the name of the relation

      - ##### m_AttributeStats

            AttributeStats[] m_AttributeStats

        Cached stats on the attributes we've summarized so far

      - ##### m_AttributeTypeLab

            JLabel m_AttributeTypeLab

        Displays the type of attribute

      - ##### m_AttributeWeightLab

            JLabel m_AttributeWeightLab

        Displays the weight of attribute

      - ##### m_DistinctLab

            JLabel m_DistinctLab

        Displays the number of distinct values

      - ##### m_Instances

            Instances m_Instances

        The instances we're playing with

      - ##### m_MissingLab

            JLabel m_MissingLab

        Displays the number of missing values

      - ##### m_StatsTable

            JTable m_StatsTable

        Displays other stats in a table

      - ##### m_UniqueLab

            JLabel m_UniqueLab

        Displays the number of unique values

      - ##### m_WeightLab

            JLabel m_WeightLab

        Displays the string "Weight:"

  - ### Class weka.gui.AttributeVisualizationPanel

    class AttributeVisualizationPanel extends PrintablePanel implements Serializable
    serialVersionUID:
      -8650490488825371193L

    - #### Serialized Fields

      - ##### m_as

            AttributeStats m_as

        This holds the attribute stats of the current attribute on display. It is calculated in setAttribute(int idx) when it is called to set a new attribute index.

      - ##### m_asCache

            AttributeStats[] m_asCache

        Cache of attribute stats info for the current data set

      - ##### m_attribIndex

            int m_attribIndex

        This holds the index of the current attribute on display and should be set through setAttribute(int idx).

      - ##### m_barRange

            double m_barRange

        Contains the range of each bar in a histogram. It is used to work out the range of bar the mouse pointer is on in getToolTipText().

      - ##### m_classIndex

            int m_classIndex

        Contains the current class index.

      - ##### m_colorAttrib

            JComboBox m_colorAttrib

        This stores and lets the user select a class attribute. It also has an entry "No Class" if the user does not want to set a class attribute for colouring.

      - ##### m_colorList

            ArrayList<Color> m_colorList

        Contains discrete colours for colouring of subbars of histograms and bar plots when the class attribute is set and is nominal

      - ##### m_data

            Instances m_data

        This holds the current set of instances

      - ##### m_displayCurrentAttribute

            boolean m_displayCurrentAttribute

      - ##### m_doneCurrentAttribute

            boolean m_doneCurrentAttribute

      - ##### m_fm

            FontMetrics m_fm

        Fontmetrics used to get the font size which is required for calculating displayable area size, bar height ratio and width of strings that are displayed on top of bars indicating their count.

      - ##### m_hc

            Thread m_hc

        This stores the BarCalc or HistCalc thread while a new barplot or histogram is being calculated.

      - ##### m_histBarClassCounts

            SparseInstance[] m_histBarClassCounts

        This array holds the per class count (or per class height) of the each of the bars in a barplot or a histogram. For nominal attributes the format is:
        m_histBarClassCounts[nominalValue][classValue+1]. For numeric attributes the format is:
        m_histBarClassCounts[interval][classValues+1],
        where the number of intervals is calculated by the Scott's method as mentioned above. The array is initialized to have 1+numClasses to accomodate for instances with missing class value. The ones with missing class value are displayed as a black sub par in a histogram or a barplot. NOTE: The values of this array are only calculated if the class attribute is set and it is nominal.

      - ##### m_histBarCounts

            double[] m_histBarCounts

        This array holds the count (or height) for the each of the bars in a barplot or a histogram. In case of barplots (and current attribute being nominal) its length (and the number of bars) is equal to the number of nominal values in the current attribute, with each field of the array being equal to the count of each nominal that it represents (the count of ith nominal value of an attribute is given by m_as.nominalWeights[i]). Whereas, in case of histograms (and current attribute being numeric) the width of its intervals is calculated by Scott's(1979) method:
        intervalWidth = Max(1, 3.49*Std.Dev*numInstances^(1/3)) And the number of intervals by:
        intervals = max(1, Math.round(Range/intervalWidth); Then each field of this array contains the number of values of the current attribute that fall in the histogram interval that it represents.
        NOTE: The values of this array are only calculated if the class attribute is not set or if it is numeric.

      - ##### m_locker

            Integer m_locker

        Lock variable to synchronize the different threads running currently in this class. There are two to three threads in this class, AWT paint thread which is handled differently in paintComponent() which checks on m_threadRun to determine if it can perform full paint or not, the second thread is the main execution thread and the third is the one represented by m_hc which we start when we want to calculate the internal fields for a bar plot or a histogram.

      - ##### m_maxValue

            double m_maxValue

        This holds the max value of the current attribute. In case of nominal attribute it is the highest count that a nominal value has in the attribute (given by m_as.nominalWeights[i]), otherwise in case of numeric attribute it is simply the maximum value present in the attribute (given by m_as.numericStats.max). It is used to calculate the ratio of the height of the bars with respect to the height of the display area.

      - ##### m_threadRun

            boolean m_threadRun

        True if the thread m_hc above is running.

  - ### Class weka.gui.CheckBoxList

    class CheckBoxList extends JList implements Serializable
    serialVersionUID:
      -4359573373359270258L

  - ### Class weka.gui.CheckBoxList.CheckBoxListModel

    class CheckBoxListModel extends DefaultListModel implements Serializable
    serialVersionUID:
      7772455499540273507L

  - ### Class weka.gui.CheckBoxList.CheckBoxListRenderer

    class CheckBoxListRenderer extends JCheckBox implements Serializable
    serialVersionUID:
      1059591605858524586L

  - ### Class weka.gui.CloseableTabTitle

    class CloseableTabTitle extends JPanel implements Serializable
    serialVersionUID:
      9178081197757118130L

    - #### Serialized Fields

      - ##### m_callback

            CloseableTabTitle.ClosingCallback m_callback

        Owner to callback on closing widget click

      - ##### m_closeAccelleratorText

            String m_closeAccelleratorText

        Description of the keyboard accellerator used for closing the active tab (if any)

      - ##### m_enclosingPane

            JTabbedPane m_enclosingPane

        The enclosing JTabbedPane

      - ##### m_tabButton

            weka.gui.CloseableTabTitle.TabButton m_tabButton

        The close widget

      - ##### m_tabLabel

            JLabel m_tabLabel

        The label for the tab

  - ### Class weka.gui.ConverterFileChooser

    class ConverterFileChooser extends WekaFileChooser implements Serializable
    serialVersionUID:
      -5373058011025481738L

    - #### Serialized Fields

      - ##### m_CapabilitiesFilter

            Capabilities m_CapabilitiesFilter

        the Capabilities filter for the savers.

      - ##### m_CheckBoxOptions

            JCheckBox m_CheckBoxOptions

        the checkbox for bringing up the GenericObjectEditor.

      - ##### m_CoreConvertersOnly

            boolean m_CoreConvertersOnly

        whether to display only core converters (hardcoded in ConverterUtils). Necessary for RMI/Remote Experiments for instance.
        See Also:
          - `ConverterResources.CORE_FILE_LOADERS`
          - `ConverterResources.CORE_FILE_SAVERS`

      - ##### m_CurrentConverter

            Object m_CurrentConverter

        the converter that was chosen by the user.

      - ##### m_DialogType

            int m_DialogType

        the type of dialog to display.

      - ##### m_Editor

            GenericObjectEditor m_Editor

        the GOE for displaying the options of a loader/saver.

      - ##### m_EditorResult

            int m_EditorResult

        whether the GOE was OKed or Canceled.

      - ##### m_FileMustExist

            boolean m_FileMustExist

        whether the file to be opened must exist (only open dialog).

      - ##### m_LastFilter

            FileFilter m_LastFilter

        the last filter that was used for opening/saving.

      - ##### m_Listener

            PropertyChangeListener m_Listener

        the propertychangelistener.

      - ##### m_OverwriteWarning

            boolean m_OverwriteWarning

        whether to popup a dialog in case the file already exists (only save dialog).

  - ### Class weka.gui.CostBenefitAnalysisPanel

    class CostBenefitAnalysisPanel extends JPanel implements Serializable
    serialVersionUID:
      5364871945448769003L

    - #### Serialized Fields

      - ##### m_benefitR

            JRadioButton m_benefitR

      - ##### m_classAttribute

            Attribute m_classAttribute

        The class attribute from the data that was used to generate the threshold curve

      - ##### m_classificationAccV

            JLabel m_classificationAccV

        Classification accuracy

      - ##### m_conf_aa

            weka.gui.CostBenefitAnalysisPanel.ConfusionCell m_conf_aa

      - ##### m_conf_ab

            weka.gui.CostBenefitAnalysisPanel.ConfusionCell m_conf_ab

      - ##### m_conf_actualA

            JLabel m_conf_actualA

      - ##### m_conf_actualB

            JLabel m_conf_actualB

      - ##### m_conf_ba

            weka.gui.CostBenefitAnalysisPanel.ConfusionCell m_conf_ba

      - ##### m_conf_bb

            weka.gui.CostBenefitAnalysisPanel.ConfusionCell m_conf_bb

      - ##### m_conf_predictedA

            JLabel m_conf_predictedA

      - ##### m_conf_predictedB

            JLabel m_conf_predictedB

      - ##### m_cost_aa

            JTextField m_cost_aa

      - ##### m_cost_ab

            JTextField m_cost_ab

      - ##### m_cost_actualA

            JLabel m_cost_actualA

      - ##### m_cost_actualB

            JLabel m_cost_actualB

      - ##### m_cost_ba

            JTextField m_cost_ba

      - ##### m_cost_bb

            JTextField m_cost_bb

      - ##### m_cost_predictedA

            JLabel m_cost_predictedA

      - ##### m_cost_predictedB

            JLabel m_cost_predictedB

      - ##### m_costBenefit

            PlotData2D m_costBenefit

        Data for the cost/benefit curve

      - ##### m_costBenefitL

            JLabel m_costBenefitL

      - ##### m_costBenefitPanel

            VisualizePanel m_costBenefitPanel

        Displays the cost/benefit (profit/loss) graph

      - ##### m_costBenefitV

            JLabel m_costBenefitV

      - ##### m_costR

            JRadioButton m_costR

      - ##### m_fnPrevious

            double m_fnPrevious

      - ##### m_fpPrevious

            double m_fpPrevious

      - ##### m_gainV

            JLabel m_gainV

      - ##### m_masterPlot

            PlotData2D m_masterPlot

        Data for the threshold curve

      - ##### m_maximizeCB

            JButton m_maximizeCB

      - ##### m_minimizeCB

            JButton m_minimizeCB

      - ##### m_originalPopSize

            int m_originalPopSize

      - ##### m_percOfTarget

            JRadioButton m_percOfTarget

      - ##### m_percOfTargetLab

            JLabel m_percOfTargetLab

      - ##### m_percPop

            JRadioButton m_percPop

      - ##### m_percPopLab

            JLabel m_percPopLab

      - ##### m_performancePanel

            VisualizePanel m_performancePanel

        Displays the performance graphs(s)

      - ##### m_previousShapeIndex

            int m_previousShapeIndex

        The index of the previous plotted point that was highlighted

      - ##### m_randomV

            JLabel m_randomV

      - ##### m_shapeSizes

            int[] m_shapeSizes

        The size of the points being plotted

      - ##### m_threshold

            JRadioButton m_threshold

      - ##### m_thresholdLab

            JLabel m_thresholdLab

      - ##### m_thresholdSlider

            JSlider m_thresholdSlider

        The slider for adjusting the threshold

      - ##### m_tnPrevious

            double m_tnPrevious

      - ##### m_totalPopField

            JTextField m_totalPopField

        Population text field

      - ##### m_totalPopPrevious

            int m_totalPopPrevious

      - ##### m_tpPrevious

            double m_tpPrevious

  - ### Class weka.gui.CostBenefitAnalysisPanel.ConfusionCell

    class ConfusionCell extends JPanel implements Serializable
    serialVersionUID:
      6148640235434494767L

    - #### Serialized Fields

      - ##### m_conf_cell

            JLabel m_conf_cell

      - ##### m_conf_perc

            JLabel m_conf_perc

      - ##### m_percentage

            double m_percentage

      - ##### m_percentageP

            JPanel m_percentageP

  - ### Class weka.gui.DatabaseConnectionDialog

    class DatabaseConnectionDialog extends JDialog implements Serializable
    serialVersionUID:
      -1081946748666245054L

    - #### Serialized Fields

      - ##### m_DbaseURLLab

            JLabel m_DbaseURLLab

      - ##### m_DbaseURLText

            JTextField m_DbaseURLText

      - ##### m_DebugCheckBox

            JCheckBox m_DebugCheckBox

      - ##### m_DebugLab

            JLabel m_DebugLab

      - ##### m_PasswordLab

            JLabel m_PasswordLab

      - ##### m_PasswordText

            JPasswordField m_PasswordText

      - ##### m_returnValue

            int m_returnValue

      - ##### m_UserNameLab

            JLabel m_UserNameLab

      - ##### m_UserNameText

            JTextField m_UserNameText

  - ### Class weka.gui.EnvironmentField

    class EnvironmentField extends JPanel implements Serializable
    serialVersionUID:
      -3125404573324734121L

    - #### Serialized Fields

      - ##### m_combo

            JComboBox m_combo

        The combo box

      - ##### m_currentCaretPos

            int m_currentCaretPos

      - ##### m_currentContents

            String m_currentContents

      - ##### m_env

            Environment m_env

        The current environment variables

      - ##### m_firstCaretPos

            int m_firstCaretPos

      - ##### m_label

            JLabel m_label

        The label for the widget

      - ##### m_previousCaretPos

            int m_previousCaretPos

      - ##### m_support

            PropertyChangeSupport m_support

  - ### Class weka.gui.EnvironmentField.WideComboBox

    class WideComboBox extends JComboBox implements Serializable
    serialVersionUID:
      -6512065375459733517L

    - #### Serialized Fields

      - ##### m_layingOut

            boolean m_layingOut

  - ### Class weka.gui.ETable

    class ETable extends JTable implements Serializable
    serialVersionUID:
      -3028630226368293049L

    - #### Serialized Fields

      - ##### MAC_FOCUSED_SELECTED_CELL_HORIZONTAL_LINE_COLOR

            Color MAC_FOCUSED_SELECTED_CELL_HORIZONTAL_LINE_COLOR

      - ##### MAC_FOCUSED_SELECTED_VERTICAL_LINE_COLOR

            Color MAC_FOCUSED_SELECTED_VERTICAL_LINE_COLOR

      - ##### MAC_FOCUSED_UNSELECTED_VERTICAL_LINE_COLOR

            Color MAC_FOCUSED_UNSELECTED_VERTICAL_LINE_COLOR

      - ##### MAC_OS_ALTERNATE_ROW_COLOR

            Color MAC_OS_ALTERNATE_ROW_COLOR

      - ##### MAC_UNFOCUSED_SELECTED_CELL_BACKGROUND_COLOR

            Color MAC_UNFOCUSED_SELECTED_CELL_BACKGROUND_COLOR

      - ##### MAC_UNFOCUSED_SELECTED_CELL_HORIZONTAL_LINE_COLOR

            Color MAC_UNFOCUSED_SELECTED_CELL_HORIZONTAL_LINE_COLOR

      - ##### MAC_UNFOCUSED_SELECTED_VERTICAL_LINE_COLOR

            Color MAC_UNFOCUSED_SELECTED_VERTICAL_LINE_COLOR

      - ##### MAC_UNFOCUSED_UNSELECTED_VERTICAL_LINE_COLOR

            Color MAC_UNFOCUSED_UNSELECTED_VERTICAL_LINE_COLOR

  - ### Class weka.gui.EvaluationMetricSelectionDialog

    class EvaluationMetricSelectionDialog extends JDialog implements Serializable
    serialVersionUID:
      4451184027143094270L

    - #### Serialized Fields

      - ##### m_selectedEvalMetrics

            List<String> m_selectedEvalMetrics

        The list of selected evaluation metrics

  - ### Class weka.gui.ExtensionFileFilter

    class ExtensionFileFilter extends FileFilter implements Serializable
    serialVersionUID:
      -5960622841390665131L

    - #### Serialized Fields

      - ##### m_Description

            String m_Description

        The text description of the types of files accepted

      - ##### m_Extension

            String[] m_Extension

        The filename extensions of accepted files

  - ### Class weka.gui.ExtensionFileFilterWithClass

    class ExtensionFileFilterWithClass extends ExtensionFileFilter implements Serializable

    - #### Serialized Fields

      - ##### m_FilterClass

            Class m_FilterClass

        the underlying class.

  - ### Class weka.gui.FileEnvironmentField

    class FileEnvironmentField extends EnvironmentField implements Serializable
    serialVersionUID:
      -233731548086207652L

    - #### Serialized Fields

      - ##### m_browseBut

            JButton m_browseBut

        The button to pop up the file dialog

      - ##### m_fileEditor

            FileEditor m_fileEditor

        File editor component

      - ##### m_fileEditorDialog

            PropertyDialog m_fileEditorDialog

        Dialog to hold the file editor

  - ### Class weka.gui.GenericObjectEditor.CapabilitiesFilterDialog

    class CapabilitiesFilterDialog extends JDialog implements Serializable
    serialVersionUID:
      -7845503345689646266L

    - #### Serialized Fields

      - ##### m_CancelButton

            JButton m_CancelButton

        the Cancel button.

      - ##### m_Capabilities

            Capabilities m_Capabilities

        the capabilities used for initializing the dialog.

      - ##### m_InfoLabel

            JLabel m_InfoLabel

        the label, listing the name of the superclass.

      - ##### m_List

            CheckBoxList m_List

        the list with all the capabilities.

      - ##### m_OkButton

            JButton m_OkButton

        the OK button.

      - ##### m_Popup

            JPopupMenu m_Popup

        the popup to display again.

      - ##### m_Self

            JDialog m_Self

        the dialog itself.

  - ### Class weka.gui.GenericObjectEditor.GOEPanel

    class GOEPanel extends JPanel implements Serializable
    serialVersionUID:
      3656028520876011335L

    - #### Serialized Fields

      - ##### m_cancelBut

            JButton m_cancelBut

        cancel button.

      - ##### m_ChildPropertySheet

            PropertySheetPanel m_ChildPropertySheet

        The component that performs classifier customization.

      - ##### m_ClassNameLabel

            JLabel m_ClassNameLabel

        The name of the current class.

      - ##### m_FileChooser

            WekaFileChooser m_FileChooser

        The filechooser for opening and saving object files.

      - ##### m_okBut

            JButton m_okBut

        ok button.

      - ##### m_OpenBut

            JButton m_OpenBut

        Open object from disk.

      - ##### m_SaveBut

            JButton m_SaveBut

        Save object to disk.

  - ### Class weka.gui.GenericObjectEditor.GOETreeNode

    class GOETreeNode extends DefaultMutableTreeNode implements Serializable
    serialVersionUID:
      -1707872446682150133L

    - #### Serialized Fields

      - ##### m_Capabilities

            Capabilities m_Capabilities

        the Capabilities object to use for filtering.

      - ##### m_toolTipText

            String m_toolTipText

        tool tip

  - ### Class weka.gui.GenericObjectEditor.JTreePopupMenu

    class JTreePopupMenu extends JPopupMenu implements Serializable
    serialVersionUID:
      -3404546329655057387L

    - #### Serialized Fields

      - ##### m_CloseButton

            JButton m_CloseButton

        The button for closing the popup again.

      - ##### m_FilterButton

            JButton m_FilterButton

        The filter button in case of CapabilitiesHandlers.

      - ##### m_RemoveFilterButton

            JButton m_RemoveFilterButton

        The remove filter button in case of CapabilitiesHandlers.

      - ##### m_scroller

            JScrollPane m_scroller

        The scroller.

      - ##### m_Self

            JPopupMenu m_Self

        the popup itself.

      - ##### m_tree

            JTree m_tree

        The tree.

  - ### Class weka.gui.GenericObjectEditorHistory

    class GenericObjectEditorHistory extends Object implements Serializable
    serialVersionUID:
      -1255734638729633595L

    - #### Serialized Fields

      - ##### m_History

            Vector<Object> m_History

        the history of objects.

  - ### Class weka.gui.GenericObjectEditorHistory.HistorySelectionEvent

    class HistorySelectionEvent extends EventObject implements Serializable
    serialVersionUID:
      45824542929908105L

    - #### Serialized Fields

      - ##### m_HistoryItem

            Object m_HistoryItem

        the selected favorite.

  - ### Class weka.gui.GUIChooserApp

    class GUIChooserApp extends JFrame implements Serializable
    serialVersionUID:
      9001529425230247914L

    - #### Serialized Fields

      - ##### m_ChildFrames

            HashSet<Container> m_ChildFrames

        contains the child frames (title <-> object).

      - ##### m_ExperimenterBut

            JButton m_ExperimenterBut

        Click to open the Explorer

      - ##### m_ExplorerBut

            JButton m_ExplorerBut

        Click to open the Explorer

      - ##### m_FileChooserGraphVisualizer

            WekaFileChooser m_FileChooserGraphVisualizer

        filechooser for the GraphVisualizer

      - ##### m_FileChooserPlot

            WekaFileChooser m_FileChooserPlot

        filechooser for Plots

      - ##### m_FileChooserROC

            WekaFileChooser m_FileChooserROC

        filechooser for ROC curves

      - ##### m_FileChooserTreeVisualizer

            WekaFileChooser m_FileChooserTreeVisualizer

        filechooser for the TreeVisualizer

      - ##### m_Frames

            Vector<JFrame> m_Frames

        The frames for the various applications that are open

      - ##### m_Icon

            Image m_Icon

        the icon for the frames

      - ##### m_jMenuBar

            JMenuBar m_jMenuBar

      - ##### m_jMenuHelp

            JMenu m_jMenuHelp

      - ##### m_jMenuProgram

            JMenu m_jMenuProgram

      - ##### m_jMenuTools

            JMenu m_jMenuTools

      - ##### m_jMenuVisualization

            JMenu m_jMenuVisualization

      - ##### m_KnowledgeFlowBut

            JButton m_KnowledgeFlowBut

        Click to open the KnowledgeFlow

      - ##### m_PanelApplications

            JPanel m_PanelApplications

        the panel for the application buttons

      - ##### m_Self

            GUIChooserApp m_Self

        the GUIChooser itself

      - ##### m_settings

            Settings m_settings

        GUIChooser settings

      - ##### m_SimpleBut

            JButton m_SimpleBut

        Click to open the simplecli

      - ##### m_weka

            Image m_weka

        The weka image

      - ##### m_WorkbenchBut

            JButton m_WorkbenchBut

        Click to open the Workbench

  - ### Class weka.gui.GUIChooserApp.ChildFrameSDI

    class ChildFrameSDI extends JFrame implements Serializable
    serialVersionUID:
      8588293938686425618L

    - #### Serialized Fields

      - ##### m_Parent

            GUIChooserApp m_Parent

        the parent frame.

  - ### Class weka.gui.GUIChooserApp.GUIChooserDefaults

    class GUIChooserDefaults extends Defaults implements Serializable
    serialVersionUID:
      -8524894440289936685L

  - ### Class weka.gui.HierarchyPropertyParser

    class HierarchyPropertyParser extends Object implements Serializable
    serialVersionUID:
      -4151103338506077544L

    - #### Serialized Fields

      - ##### m_Current

            weka.gui.HierarchyPropertyParser.TreeNode m_Current

        Keep track of the current node when traversing the tree

      - ##### m_Depth

            int m_Depth

        The depth of the tree

      - ##### m_Root

            weka.gui.HierarchyPropertyParser.TreeNode m_Root

        Keep track of the root of the tree

      - ##### m_Seperator

            String m_Seperator

        The level separate in the path

  - ### Class weka.gui.InstancesSummaryPanel

    class InstancesSummaryPanel extends JPanel implements Serializable
    serialVersionUID:
      -5243579535296681063L

    - #### Serialized Fields

      - ##### m_Instances

            Instances m_Instances

        The instances we're playing with

      - ##### m_NumAttributesLab

            JLabel m_NumAttributesLab

        Displays the number of attributes

      - ##### m_NumInstancesLab

            JLabel m_NumInstancesLab

        Displays the number of instances

      - ##### m_RelationNameLab

            JLabel m_RelationNameLab

        Displays the name of the relation

      - ##### m_showZeroInstancesAsUnknown

            boolean m_showZeroInstancesAsUnknown

        Whether to display 0 or ? for the number of instances in cases where a dataset has only structure. Depending on where this panel is used from, the user may have loaded a dataset with no instances or a Loader that can read incrementally may be being used (in which case we don't know how many instances are in the dataset... yet).

      - ##### m_sumOfWeightsLab

            JLabel m_sumOfWeightsLab

        Displays the sum of instance weights

  - ### Class weka.gui.InteractiveTableModel

    class InteractiveTableModel extends AbstractTableModel implements Serializable
    serialVersionUID:
      -5113873323690309667L

    - #### Serialized Fields

      - ##### m_columnNames

            String[] m_columnNames

        The names of the columns

      - ##### m_dataVector

            List<List<String>> m_dataVector

        Holds the data

      - ##### m_hidden_index

            int m_hidden_index

        Index of the hidden column

  - ### Class weka.gui.InteractiveTablePanel

    class InteractiveTablePanel extends JPanel implements Serializable
    serialVersionUID:
      4495705463732140410L

    - #### Serialized Fields

      - ##### m_columnNames

            String[] m_columnNames

        Holds column names

      - ##### m_scroller

            JScrollPane m_scroller

        Scroll panel for the table

      - ##### m_table

            JTable m_table

        The table itself

      - ##### m_tableModel

            InteractiveTableModel m_tableModel

        Model for the table

  - ### Class weka.gui.ListSelectorDialog

    class ListSelectorDialog extends JDialog implements Serializable
    serialVersionUID:
      906147926840288895L

    - #### Serialized Fields

      - ##### m_CancelBut

            JButton m_CancelBut

        Click to cancel the property selection

      - ##### m_List

            JList m_List

        The list component

      - ##### m_PatternBut

            JButton m_PatternBut

        Click to enter a regex pattern for selection

      - ##### m_PatternRegEx

            String m_PatternRegEx

        The current regular expression.

      - ##### m_Result

            int m_Result

        Whether the selection was made or cancelled

      - ##### m_SelectBut

            JButton m_SelectBut

        Click to choose the currently selected property

  - ### Class weka.gui.LogPanel

    class LogPanel extends JPanel implements Serializable
    serialVersionUID:
      -4072464549112439484L

    - #### Serialized Fields

      - ##### m_First

            boolean m_First

        An indicator for whether text has been output yet

      - ##### m_Frame

            JFrame m_Frame

        The JFrame to use

      - ##### m_logButton

            JButton m_logButton

        The button for viewing the log

      - ##### m_LogText

            JTextArea m_LogText

        Displays the log messages

      - ##### m_StatusLab

            JLabel m_StatusLab

        Displays the current status

      - ##### m_TaskMonitor

            WekaTaskMonitor m_TaskMonitor

        The panel for monitoring the number of running tasks (if supplied)

  - ### Class weka.gui.LogWindow

    class LogWindow extends JFrame implements Serializable
    serialVersionUID:
      5650947361381061112L

    - #### Serialized Fields

      - ##### m_ButtonClear

            JButton m_ButtonClear

        the clear button

      - ##### m_ButtonClose

            JButton m_ButtonClose

        the close button

      - ##### m_CheckBoxWordwrap

            JCheckBox m_CheckBoxWordwrap

        whether to allow wordwrap or not

      - ##### m_LabelCurrentSize

            JLabel m_LabelCurrentSize

        the current size

      - ##### m_Output

            JTextPane m_Output

        the output

      - ##### m_SpinnerMaxSize

            JSpinner m_SpinnerMaxSize

        the spinner for the max number of chars

      - ##### m_UseWordwrap

            boolean m_UseWordwrap

        whether the JTextPane has wordwrap or not

  - ### Class weka.gui.Main

    class Main extends JFrame implements Serializable
    serialVersionUID:
      1453813254824253849L

    - #### Serialized Fields

      - ##### jDesktopPane

            JDesktopPane jDesktopPane

      - ##### jMenuApplications

            JMenu jMenuApplications

      - ##### jMenuBar

            JMenuBar jMenuBar

      - ##### jMenuExtensions

            JMenu jMenuExtensions

      - ##### jMenuHelp

            JMenu jMenuHelp

      - ##### jMenuItemApplicationsExperimenter

            JMenuItem jMenuItemApplicationsExperimenter

      - ##### jMenuItemApplicationsExplorer

            JMenuItem jMenuItemApplicationsExplorer

      - ##### jMenuItemApplicationsKnowledgeFlow

            JMenuItem jMenuItemApplicationsKnowledgeFlow

      - ##### jMenuItemApplicationsSimpleCLI

            JMenuItem jMenuItemApplicationsSimpleCLI

      - ##### jMenuItemHelpAbout

            JMenuItem jMenuItemHelpAbout

      - ##### jMenuItemHelpHomepage

            JMenuItem jMenuItemHelpHomepage

      - ##### jMenuItemHelpSourceforge

            JMenuItem jMenuItemHelpSourceforge

      - ##### jMenuItemHelpSystemInfo

            JMenuItem jMenuItemHelpSystemInfo

      - ##### jMenuItemHelpWekaWiki

            JMenuItem jMenuItemHelpWekaWiki

      - ##### jMenuItemProgramExit

            JMenuItem jMenuItemProgramExit

      - ##### jMenuItemProgramLogWindow

            JMenuItem jMenuItemProgramLogWindow

      - ##### jMenuItemProgramMemoryUsage

            JMenuItem jMenuItemProgramMemoryUsage

      - ##### jMenuItemToolsArffViewer

            JMenuItem jMenuItemToolsArffViewer

      - ##### jMenuItemToolsGroovyConsole

            JMenuItem jMenuItemToolsGroovyConsole

      - ##### jMenuItemToolsJythonConsole

            JMenuItem jMenuItemToolsJythonConsole

      - ##### jMenuItemToolsSqlViewer

            JMenuItem jMenuItemToolsSqlViewer

      - ##### jMenuItemVisualizationBoundaryVisualizer

            JMenuItem jMenuItemVisualizationBoundaryVisualizer

      - ##### jMenuItemVisualizationGraphVisualizer

            JMenuItem jMenuItemVisualizationGraphVisualizer

      - ##### jMenuItemVisualizationPlot

            JMenuItem jMenuItemVisualizationPlot

      - ##### jMenuItemVisualizationROC

            JMenuItem jMenuItemVisualizationROC

      - ##### jMenuItemVisualizationTreeVisualizer

            JMenuItem jMenuItemVisualizationTreeVisualizer

      - ##### jMenuProgram

            JMenu jMenuProgram

      - ##### jMenuTools

            JMenu jMenuTools

      - ##### jMenuVisualization

            JMenu jMenuVisualization

      - ##### jMenuWindows

            JMenu jMenuWindows

      - ##### m_ChildFrames

            HashSet<Container> m_ChildFrames

        contains the child frames (title <-> object).

      - ##### m_FileChooserGraphVisualizer

            WekaFileChooser m_FileChooserGraphVisualizer

        filechooser for the GraphVisualizer.

      - ##### m_FileChooserPlot

            WekaFileChooser m_FileChooserPlot

        filechooser for Plots.

      - ##### m_FileChooserROC

            WekaFileChooser m_FileChooserROC

        filechooser for ROC curves.

      - ##### m_FileChooserTreeVisualizer

            WekaFileChooser m_FileChooserTreeVisualizer

        filechooser for the TreeVisualizer.

      - ##### m_GUIType

            int m_GUIType

        the type of GUI to display.

      - ##### m_Self

            Main m_Self

        the frame itself.

  - ### Class weka.gui.Main.BackgroundDesktopPane

    class BackgroundDesktopPane extends JDesktopPane implements Serializable
    serialVersionUID:
      2046713123452402745L

    - #### Serialized Fields

      - ##### m_Background

            Image m_Background

        the actual background image.

  - ### Class weka.gui.Main.ChildFrameMDI

    class ChildFrameMDI extends JInternalFrame implements Serializable
    serialVersionUID:
      3772573515346899959L

    - #### Serialized Fields

      - ##### m_Parent

            Main m_Parent

        the parent frame.

  - ### Class weka.gui.Main.ChildFrameSDI

    class ChildFrameSDI extends JFrame implements Serializable
    serialVersionUID:
      8588293938686425618L

    - #### Serialized Fields

      - ##### m_Parent

            Main m_Parent

        the parent frame.

  - ### Class weka.gui.MemoryUsagePanel

    class MemoryUsagePanel extends JPanel implements Serializable
    serialVersionUID:
      -4812319791687471721L

    - #### Serialized Fields

      - ##### m_BackgroundColor

            Color m_BackgroundColor

        the background color.

      - ##### m_ButtonGC

            JButton m_ButtonGC

        the button for running the garbage collector.

      - ##### m_Colors

            Hashtable<Double,Color> m_Colors

        the corresponding colors for the thresholds.

      - ##### m_DefaultColor

            Color m_DefaultColor

        the default color.

      - ##### m_FrameLocation

            Point m_FrameLocation

        the position for the dialog.

      - ##### m_History

            Vector<Double> m_History

        the memory usage over time.

      - ##### m_Memory

            Memory m_Memory

        for monitoring the memory usage.

      - ##### m_Monitor

            weka.gui.MemoryUsagePanel.MemoryMonitor m_Monitor

        the thread for monitoring the memory usage.

      - ##### m_Percentages

            Vector<Double> m_Percentages

        the threshold percentages to change color.

  - ### Class weka.gui.PackageManager

    class PackageManager extends JPanel implements Serializable
    serialVersionUID:
      -7463821313750352385L

    - #### Serialized Fields

      - ##### m_allBut

            JRadioButton m_allBut

        All radio button

      - ##### m_allPackages

            List<Package> m_allPackages

      - ##### m_availableBut

            JRadioButton m_availableBut

        Available radio button

      - ##### m_availablePackages

            List<Package> m_availablePackages

      - ##### m_backB

            JButton m_backB

      - ##### m_browserHistory

            LinkedList<URL> m_browserHistory

      - ##### m_browserTools

            JToolBar m_browserTools

      - ##### m_cacheEstablished

            boolean m_cacheEstablished

      - ##### m_cacheRefreshInProgress

            boolean m_cacheRefreshInProgress

      - ##### m_detailLabel

            JLabel m_detailLabel

      - ##### m_forceBut

            JCheckBox m_forceBut

      - ##### m_homeB

            JButton m_homeB

      - ##### m_infoPane

            JEditorPane m_infoPane

        An editor pane to display package information

      - ##### m_installBut

            JButton m_installBut

        Button for installing the selected package

      - ##### m_installedBut

            JRadioButton m_installedBut

        Installed radio button

      - ##### m_installedPackages

            List<Package> m_installedPackages

      - ##### m_installing

            boolean m_installing

      - ##### m_model

            DefaultTableModel m_model

      - ##### m_newPackagesAvailableL

            JLabel m_newPackagesAvailableL

      - ##### m_packageComparator

            Comparator<Package> m_packageComparator

      - ##### m_packageDescriptions

            Map<String,String> m_packageDescriptions

      - ##### m_packageLookupInfo

            Map<String,List<Object>> m_packageLookupInfo

      - ##### m_progress

            JProgressBar m_progress

      - ##### m_refreshCacheBut

            JButton m_refreshCacheBut

        Button for refreshing the package meta data cache

      - ##### m_reverseSort

            boolean m_reverseSort

        Reverse the sort order if the user clicks the same column header twice

      - ##### m_searchField

            JTextField m_searchField

      - ##### m_searchHitsLab

            JLabel m_searchHitsLab

      - ##### m_searchResults

            List<Package> m_searchResults

      - ##### m_sortColumn

            int m_sortColumn

        The column in the table to sort the entries by

      - ##### m_splitP

            JSplitPane m_splitP

      - ##### m_table

            JTable m_table

        The JTable for displaying the package names and version numbers

      - ##### m_toggleLoad

            JButton m_toggleLoad

        Button for toggling the load status of an installed package

      - ##### m_uninstallBut

            JButton m_uninstallBut

        Button for uninstalling the selected package

      - ##### m_unofficialBut

            JButton m_unofficialBut

        Button to pop up the file environment field widget

      - ##### m_unofficialChooser

            FileEnvironmentField m_unofficialChooser

        Widget for specifying a URL or path to an unofficial package to install

      - ##### m_unofficialFrame

            JFrame m_unofficialFrame

  - ### Class weka.gui.PackageManager.ComboBoxEditor

    class ComboBoxEditor extends DefaultCellEditor implements Serializable
    serialVersionUID:
      5240331667759901966L

  - ### Class weka.gui.PasswordField

    class PasswordField extends JPanel implements Serializable
    serialVersionUID:
      8180782063577036194L

    - #### Serialized Fields

      - ##### m_label

            JLabel m_label

        The label for the widget

      - ##### m_password

            JPasswordField m_password

        The password field

      - ##### m_support

            PropertyChangeSupport m_support

  - ### Class weka.gui.PerspectiveManager

    class PerspectiveManager extends JPanel implements Serializable
    serialVersionUID:
      -6099806469970666208L

    - #### Serialized Fields

      - ##### m_allowedPerspectiveClassPrefixes

            List<String> m_allowedPerspectiveClassPrefixes

        Allow these perspectives in the toolbar (empty list means allow all)

      - ##### m_appMenuBar

            JMenuBar m_appMenuBar

        Main application menu bar

      - ##### m_configAndPerspectivesToolBar

            JPanel m_configAndPerspectivesToolBar

        Holds the config/settings button and toolbar

      - ##### m_configAndPerspectivesVisible

            boolean m_configAndPerspectivesVisible

        Whether the toolbar is visible or hidden

      - ##### m_disallowedPerspectiveClassPrefixes

            List<String> m_disallowedPerspectiveClassPrefixes

        Disallow these perspectives (non-empty list overrides meaning of empty allowed list)

      - ##### m_LogPanel

            LogPanel m_LogPanel

        The panel for log and status messages

      - ##### m_logVisible

            boolean m_logVisible

        Whether the log is visible in the current perspective

      - ##### m_mainApp

            GUIApplication m_mainApp

        The main application that owns this perspective manager

      - ##### m_mainPerspective

            Perspective m_mainPerspective

        The main perspective for the application owning this perspective manager

      - ##### m_perspectiveCache

            Map<String,Perspective> m_perspectiveCache

        Cache of perspectives

      - ##### m_perspectiveGroup

            ButtonGroup m_perspectiveGroup

        For grouping the perspectives buttons in the toolbar

      - ##### m_perspectiveNameLookup

            Map<String,String> m_perspectiveNameLookup

        Name lookup for perspectives

      - ##### m_perspectives

            List<Perspective> m_perspectives

        The perspectives that have a button in the toolbar

      - ##### m_perspectiveToolBar

            JToolBar m_perspectiveToolBar

        The actual perspectives toolbar

      - ##### m_programMenu

            JMenu m_programMenu

        Program menu

      - ##### m_togglePerspectivesToolBar

            JMenuItem m_togglePerspectivesToolBar

        Menu item for toggling whether the toolbar is visible or not

      - ##### m_visiblePerspectives

            LinkedHashSet<String> m_visiblePerspectives

        Names of visible perspectives (i.e. those that the user has opted to be available via a button in the toolbar

  - ### Class weka.gui.PerspectiveManager.SelectedPerspectivePreferences

    class SelectedPerspectivePreferences extends Object implements Serializable
    serialVersionUID:
      -2665480123235382483L

    - #### Serialized Fields

      - ##### m_perspectivesToolbarAlwaysHidden

            boolean m_perspectivesToolbarAlwaysHidden

        Whether the toolbar should always be hidden (and not able to be toggled from the menu or widget.

      - ##### m_perspectivesToolbarVisibleOnStartup

            boolean m_perspectivesToolbarVisibleOnStartup

        Whether the toolbar should be visible (or hidden) at startup

      - ##### m_userVisiblePerspectives

            LinkedList<String> m_userVisiblePerspectives

        List of user selected perspectives to show

  - ### Class weka.gui.PropertyDialog

    class PropertyDialog extends JDialog implements Serializable
    serialVersionUID:
      -2314850859392433539L

    - #### Serialized Fields

      - ##### m_Editor

            PropertyEditor m_Editor

        The property editor.

      - ##### m_EditorComponent

            Component m_EditorComponent

        The custom editor component.

  - ### Class weka.gui.PropertyPanel

    class PropertyPanel extends JPanel implements Serializable
    serialVersionUID:
      5370025273466728904L

    - #### Serialized Fields

      - ##### m_CustomPanel

            JPanel m_CustomPanel

        The custom panel (if any)

      - ##### m_Editor

            PropertyEditor m_Editor

        The property editor

      - ##### m_HasCustomPanel

            boolean m_HasCustomPanel

        Whether the editor has provided its own panel

      - ##### m_PD

            PropertyDialog m_PD

        The currently displayed property dialog, if any

  - ### Class weka.gui.PropertySelectorDialog

    class PropertySelectorDialog extends JDialog implements Serializable
    serialVersionUID:
      -3155058124137930518L

    - #### Serialized Fields

      - ##### m_CancelBut

            JButton m_CancelBut

        Click to cancel the property selection

      - ##### m_Result

            int m_Result

        Whether the selection was made or cancelled

      - ##### m_ResultPath

            Object[] m_ResultPath

        Stores the path to the selected property

      - ##### m_Root

            DefaultMutableTreeNode m_Root

        The root of the property tree

      - ##### m_RootObject

            Object m_RootObject

        The object at the root of the tree

      - ##### m_SelectBut

            JButton m_SelectBut

        Click to choose the currently selected property

      - ##### m_Tree

            JTree m_Tree

        The component displaying the property tree

  - ### Class weka.gui.PropertySheetPanel

    class PropertySheetPanel extends JPanel implements Serializable
    serialVersionUID:
      -8939835593429918345L

    - #### Serialized Fields

      - ##### m_aboutPanel

            JPanel m_aboutPanel

        The panel holding global info and help, if provided by the object being editied.

      - ##### m_CapabilitiesBut

            JButton m_CapabilitiesBut

        Button to pop up the capabilities in a separate dialog.

      - ##### m_CapabilitiesDialog

            weka.gui.PropertySheetPanel.CapabilitiesHelpDialog m_CapabilitiesDialog

        Capabilities Help dialog.

      - ##### m_CapabilitiesText

            JTextArea m_CapabilitiesText

        the TextArea of the Capabilities help dialog.

      - ##### m_Customizer

            GOECustomizer m_Customizer

        Holds the customizer (if one exists) for the object being edited

      - ##### m_Editors

            PropertyEditor[] m_Editors

        Holds property editors of the object.

      - ##### m_HelpBut

            JButton m_HelpBut

        Button to pop up the full help text in a separate dialog.

      - ##### m_HelpDialog

            JDialog m_HelpDialog

        Help dialog.

      - ##### m_HelpText

            StringBuffer m_HelpText

        StringBuffer containing help text for the object being edited.

      - ##### m_Labels

            JLabel[] m_Labels

        The labels for each property.

      - ##### m_Methods

            MethodDescriptor[] m_Methods

        Holds the methods of the target.

      - ##### m_NumEditable

            int m_NumEditable

        A count of the number of properties we have an editor for.

      - ##### m_Properties

            PropertyDescriptor[] m_Properties

        Holds properties of the target.

      - ##### m_propertyGroupingCategory

            String m_propertyGroupingCategory

        Non-empty if this panel is being used to group/display properties for a particular category

      - ##### m_showAboutPanel

            boolean m_showAboutPanel

        Whether to show the about panel

      - ##### m_Target

            Object m_Target

        The target object being edited.

      - ##### m_TipTexts

            String[] m_TipTexts

        The tool tip text for each property.

      - ##### m_useEnvironmentPropertyEditors

            boolean m_useEnvironmentPropertyEditors

        Whether to use EnvironmentField and FileEnvironmentField for text and file properties respectively

      - ##### m_Values

            Object[] m_Values

        Holds current object values for each property.

      - ##### m_Views

            JComponent[] m_Views

        Stores GUI components containing each editing component.

      - ##### support

            PropertyChangeSupport support

        A support object for handling property change listeners.

  - ### Class weka.gui.PropertySheetPanel.CapabilitiesHelpDialog

    class CapabilitiesHelpDialog extends JDialog implements Serializable
    serialVersionUID:
      -1404770987103289858L

    - #### Serialized Fields

      - ##### m_Self

            weka.gui.PropertySheetPanel.CapabilitiesHelpDialog m_Self

        the dialog itself.

  - ### Class weka.gui.ResultHistoryPanel

    class ResultHistoryPanel extends JPanel implements Serializable
    serialVersionUID:
      4297069440135326829L

    - #### Serialized Fields

      - ##### m_FramedOutput

            Hashtable<String,JTextArea> m_FramedOutput

        A Hashtable mapping names to output text components

      - ##### m_HandleRightClicks

            boolean m_HandleRightClicks

        Let the result history list handle right clicks in the default manner---ie, pop up a window displaying the buffer

      - ##### m_List

            JList m_List

        The list component

      - ##### m_Model

            DefaultListModel m_Model

        The list model

      - ##### m_Objs

            Hashtable<String,Object> m_Objs

        A hashtable mapping names to arbitrary objects

      - ##### m_Printer

            PrintableComponent m_Printer

        for printing the output to files

      - ##### m_Results

            Hashtable<String,StringBuffer> m_Results

        A Hashtable mapping names to result buffers

      - ##### m_SingleName

            String m_SingleName

        The named result being viewed in the single-click display

      - ##### m_SingleText

            JTextComponent m_SingleText

        An optional component for single-click display

  - ### Class weka.gui.ResultHistoryPanel.RKeyAdapter

    class RKeyAdapter extends KeyAdapter implements Serializable
    serialVersionUID:
      -8675332541861828079L

  - ### Class weka.gui.ResultHistoryPanel.RMouseAdapter

    class RMouseAdapter extends MouseAdapter implements Serializable
    serialVersionUID:
      -8991922650552358669L

  - ### Class weka.gui.SetInstancesPanel

    class SetInstancesPanel extends JPanel implements Serializable
    serialVersionUID:
      -384804041420453735L

    - #### Serialized Fields

      - ##### m_ClassComboBox

            JComboBox m_ClassComboBox

        the class combobox.

      - ##### m_ClassLabel

            JLabel m_ClassLabel

        the label for the class combobox.

      - ##### m_CloseBut

            JButton m_CloseBut

        Click to close the dialog.

      - ##### m_CloseButPanel

            JPanel m_CloseButPanel

        the panel the Close-Button is located in.

      - ##### m_FileChooser

            ConverterFileChooser m_FileChooser

        The file chooser for selecting arff files.

      - ##### m_Instances

            Instances m_Instances

        The current set of instances loaded.

      - ##### m_IOThread

            Thread m_IOThread

        The thread we do loading in.

      - ##### m_LastURL

            String m_LastURL

        Stores the last URL that instances were loaded from.

      - ##### m_Loader

            Loader m_Loader

        The current loader used to obtain the current instances.

      - ##### m_OpenFileBut

            JButton m_OpenFileBut

        Click to open instances from a file.

      - ##### m_OpenURLBut

            JButton m_OpenURLBut

        Click to open instances from a URL.

      - ##### m_ParentFrame

            JFrame m_ParentFrame

        the parent frame. if one is provided, the close-button is displayed

      - ##### m_readIncrementally

            boolean m_readIncrementally

        whether to read the instances incrementally, if possible.

      - ##### m_showClassComboBox

            boolean m_showClassComboBox

        whether to display a combobox that allows the user to choose the class attribute.

      - ##### m_showZeroInstancesAsUnknown

            boolean m_showZeroInstancesAsUnknown

        whether to display zero instances as unknown ("?").

      - ##### m_Summary

            InstancesSummaryPanel m_Summary

        The instance summary component.

      - ##### m_Support

            PropertyChangeSupport m_Support

        Manages sending notifications to people when we change the set of working instances.

  - ### Class weka.gui.SettingsEditor

    class SettingsEditor extends JPanel implements Serializable
    serialVersionUID:
      1453121012707399758L

    - #### Serialized Fields

      - ##### m_ownerApp

            GUIApplication m_ownerApp

      - ##### m_perspectiveEditors

            List<SettingsEditor.SingleSettingsEditor> m_perspectiveEditors

      - ##### m_perspectiveSelector

            weka.gui.SettingsEditor.PerspectiveSelector m_perspectiveSelector

      - ##### m_settings

            Settings m_settings

      - ##### m_settingsTabs

            JTabbedPane m_settingsTabs

  - ### Class weka.gui.SettingsEditor.PerspectiveSelector

    class PerspectiveSelector extends JPanel implements Serializable
    serialVersionUID:
      -4765015948030757897L

    - #### Serialized Fields

      - ##### m_perspectiveChecks

            List<JCheckBox> m_perspectiveChecks

      - ##### m_toolBarVisibleOnStartup

            JCheckBox m_toolBarVisibleOnStartup

  - ### Class weka.gui.SettingsEditor.PickList

    class PickList extends JPanel implements Serializable
    serialVersionUID:
      3505647427533464230L

    - #### Serialized Fields

      - ##### m_list

            JComboBox<String> m_list

  - ### Class weka.gui.SettingsEditor.SingleSettingsEditor

    class SingleSettingsEditor extends JPanel implements Serializable
    serialVersionUID:
      8896265984902770239L

    - #### Serialized Fields

      - ##### m_editorMap

            Map<Settings.SettingKey,PropertyEditor> m_editorMap

      - ##### m_perspSettings

            Map<Settings.SettingKey,Object> m_perspSettings

  - ### Class weka.gui.SimpleCLI

    class SimpleCLI extends JFrame implements Serializable
    serialVersionUID:
      -50661410800566036L

  - ### Class weka.gui.SimpleCLIPanel

    class SimpleCLIPanel extends ScriptingPanel implements Serializable
    serialVersionUID:
      1089039734615114942L

    - #### Serialized Fields

      - ##### m_CommandHistory

            Vector<String> m_CommandHistory

        The history of commands entered interactively.

      - ##### m_Completion

            SimpleCLIPanel.CommandlineCompletion m_Completion

        The commandline completion.

      - ##### m_HistoryPos

            int m_HistoryPos

        The current position in the command history.

      - ##### m_Input

            JTextField m_Input

        The command input area.

      - ##### m_mainApp

            GUIApplication m_mainApp

        Main application (if any) owning this perspective

      - ##### m_OutputArea

            JTextPane m_OutputArea

        The output area canvas added to the frame.

      - ##### m_perspectiveIcon

            Icon m_perspectiveIcon

        The Icon for this perspective

      - ##### m_RunThread

            Thread m_RunThread

        The thread currently running a class main method.

      - ##### m_Variables

            Map<String,Object> m_Variables

        for storing variables.

  - ### Class weka.gui.SortedTableModel

    class SortedTableModel extends AbstractTableModel implements Serializable
    serialVersionUID:
      4030907921461127548L

    - #### Serialized Fields

      - ##### mAscending

            boolean mAscending

        whether sorting is ascending or descending

      - ##### mIndices

            int[] mIndices

        the mapping between displayed and actual index

      - ##### mModel

            TableModel mModel

        the actual table model

      - ##### mSortColumn

            int mSortColumn

        the sort column

  - ### Class weka.gui.SplashWindow

    class SplashWindow extends Window implements Serializable
    serialVersionUID:
      -2685134277041307795L

    - #### Serialized Fields

      - ##### image

            Image image

        The splash image which is displayed on the splash window.

      - ##### message

            List<String> message

        Any message to overlay on the image

      - ##### paintCalled

            boolean paintCalled

        This attribute indicates whether the method paint(Graphics) has been called at least once since the construction of this window.
        This attribute is used to notify method splash(Image) that the window has been drawn at least once by the AWT event dispatcher thread.
        This attribute acts like a latch. Once set to true, it will never be changed back to false again.
        See Also:
          - `SplashWindow.paint(java.awt.Graphics)`
          - `SplashWindow.splash(java.awt.Image, java.util.List<java.lang.String>)`

  - ### Class weka.gui.ViewerDialog

    class ViewerDialog extends JDialog implements Serializable
    serialVersionUID:
      6747718484736047752L

    - #### Serialized Fields

      - ##### m_addInstanceButton

            JButton m_addInstanceButton

        Click to add a new instance to the end of the dataset

      - ##### m_ArffPanel

            ArffPanel m_ArffPanel

        the panel to display the Instances-object

      - ##### m_CancelButton

            JButton m_CancelButton

        Click to cancel the dialog

      - ##### m_OkButton

            JButton m_OkButton

        Click to activate the current set parameters

      - ##### m_Result

            int m_Result

        the result of the user's action, either OK or CANCEL

      - ##### m_UndoButton

            JButton m_UndoButton

        Click to undo the last action

  - ### Class weka.gui.WekaFileChooser

    class WekaFileChooser extends JFileChooser implements Serializable

    - #### Serialized Fields

      - ##### m_AccessoryPanel

            JPanel m_AccessoryPanel

        the accessory panel.

      - ##### m_BookmarksPanel

            WekaFileChooser.FileChooserBookmarksPanel m_BookmarksPanel

        the bookmarks.

  - ### Class weka.gui.WekaFileChooser.Factory

    class Factory extends com.googlecode.jfilechooserbookmarks.DefaultFactory implements Serializable

  - ### Class weka.gui.WekaFileChooser.FileChooserBookmarksPanel

    class FileChooserBookmarksPanel extends com.googlecode.jfilechooserbookmarks.AbstractBookmarksPanel implements Serializable

  - ### Class weka.gui.WekaFileChooser.PropertiesHandler

    class PropertiesHandler extends com.googlecode.jfilechooserbookmarks.AbstractPropertiesHandler implements Serializable

  - ### Class weka.gui.WekaTaskMonitor

    class WekaTaskMonitor extends JPanel implements Serializable
    serialVersionUID:
      508309816292197578L

    - #### Serialized Fields

      - ##### m_ActiveTasks

            int m_ActiveTasks

        The number of running weka threads

      - ##### m_animating

            boolean m_animating

        True if their are active tasks

      - ##### m_iconAnimated

            ImageIcon m_iconAnimated

        The icon for the animated bird

      - ##### m_iconStationary

            ImageIcon m_iconStationary

        The icon for the stationary bird

      - ##### m_MonitorLabel

            JLabel m_MonitorLabel

        The label for displaying info

  - ### Class weka.gui.WorkbenchApp

    class WorkbenchApp extends AbstractGUIApplication implements Serializable
    serialVersionUID:
      -2357486011273897728L

    - #### Serialized Fields

      - ##### m_mainPerspective

            PreprocessPanel m_mainPerspective

        The main perspective for this application

      - ##### m_workbenchSettings

            Settings m_workbenchSettings

        Settings for the Workbench

  - ### Class weka.gui.WorkbenchDefaults

    class WorkbenchDefaults extends Defaults implements Serializable
    serialVersionUID:
      7881327795923189743L

  - ### Class weka.gui.WrapLayout

    class WrapLayout extends FlowLayout implements Serializable
    serialVersionUID:
      7055023419450383821L

    - #### Serialized Fields

      - ##### preferredLayoutSize

            Dimension preferredLayoutSize

- ## Package weka.gui.arffviewer

  - ### Class weka.gui.arffviewer.ArffPanel

    class ArffPanel extends JPanel implements Serializable
    serialVersionUID:
      -4697041150989513939L

    - #### Serialized Fields

      - ##### m_Changed

            boolean m_Changed

        flag for whether data got changed

      - ##### m_ChangeListeners

            HashSet<ChangeListener> m_ChangeListeners

        the listeners that listen for modifications

      - ##### m_CurrentCol

            int m_CurrentCol

        the currently selected column

      - ##### m_Filename

            String m_Filename

        the filename used in the title

      - ##### m_LabelName

            JLabel m_LabelName

        displays the relation name

      - ##### m_LastReplace

            String m_LastReplace

        the string used in the last replace

      - ##### m_LastSearch

            String m_LastSearch

        the string used in the last search

      - ##### m_PopupHeader

            JPopupMenu m_PopupHeader

        the popup menu for the header row

      - ##### m_PopupRows

            JPopupMenu m_PopupRows

        the popup menu for the data rows

      - ##### m_ShowAttributeIndex

            boolean m_ShowAttributeIndex

        whether to display the attribute index in the table header.

      - ##### m_TableArff

            ArffTable m_TableArff

        the underlying table

      - ##### m_Title

            String m_Title

        the title prefix

      - ##### menuItemAttributeAsClass

            JMenuItem menuItemAttributeAsClass

      - ##### menuItemClearSearch

            JMenuItem menuItemClearSearch

      - ##### menuItemCopy

            JMenuItem menuItemCopy

      - ##### menuItemDeleteAllSelectedInstances

            JMenuItem menuItemDeleteAllSelectedInstances

      - ##### menuItemDeleteAttribute

            JMenuItem menuItemDeleteAttribute

      - ##### menuItemDeleteAttributes

            JMenuItem menuItemDeleteAttributes

      - ##### menuItemDeleteSelectedInstance

            JMenuItem menuItemDeleteSelectedInstance

      - ##### menuItemInsertInstance

            JMenuItem menuItemInsertInstance

      - ##### menuItemMean

            JMenuItem menuItemMean

      - ##### menuItemOptimalColWidth

            JMenuItem menuItemOptimalColWidth

      - ##### menuItemOptimalColWidths

            JMenuItem menuItemOptimalColWidths

      - ##### menuItemRenameAttribute

            JMenuItem menuItemRenameAttribute

      - ##### menuItemReplaceValues

            JMenuItem menuItemReplaceValues

      - ##### menuItemSearch

            JMenuItem menuItemSearch

      - ##### menuItemSetAllValues

            JMenuItem menuItemSetAllValues

      - ##### menuItemSetAttributeWeight

            JMenuItem menuItemSetAttributeWeight

      - ##### menuItemSetInstanceWeight

            JMenuItem menuItemSetInstanceWeight

      - ##### menuItemSetMissingValues

            JMenuItem menuItemSetMissingValues

      - ##### menuItemSortInstances

            JMenuItem menuItemSortInstances

      - ##### menuItemUndo

            JMenuItem menuItemUndo

  - ### Class weka.gui.arffviewer.ArffSortedTableModel

    class ArffSortedTableModel extends SortedTableModel implements Serializable
    serialVersionUID:
      -5733148376354254030L

  - ### Class weka.gui.arffviewer.ArffTable

    class ArffTable extends JTable implements Serializable
    serialVersionUID:
      -2016200506908637967L

    - #### Serialized Fields

      - ##### m_ChangeListeners

            HashSet<ChangeListener> m_ChangeListeners

        the listeners for changes

      - ##### m_SearchString

            String m_SearchString

        the search string

  - ### Class weka.gui.arffviewer.ArffTable.RelationalCellEditor

    class RelationalCellEditor extends AbstractCellEditor implements Serializable
    serialVersionUID:
      657969163293205963L

    - #### Serialized Fields

      - ##### m_Button

            JButton m_Button

        the button for opening the dialog

      - ##### m_ColumnIndex

            int m_ColumnIndex

        the column index this editor is for

      - ##### m_CurrentInst

            Instances m_CurrentInst

        the current instances

      - ##### m_RowIndex

            int m_RowIndex

        the row index this editor is for

  - ### Class weka.gui.arffviewer.ArffTableCellRenderer

    class ArffTableCellRenderer extends DefaultTableCellRenderer implements Serializable
    serialVersionUID:
      9195794493301191171L

    - #### Serialized Fields

      - ##### highlightColor

            Color highlightColor

        the color for highlighted values

      - ##### highlightColorSelected

            Color highlightColorSelected

        the color for selected highlighted values

      - ##### missingColor

            Color missingColor

        the color for missing values

      - ##### missingColorSelected

            Color missingColorSelected

        the color for selected missing values

  - ### Class weka.gui.arffviewer.ArffTableModel

    class ArffTableModel extends DefaultTableModel implements Serializable
    serialVersionUID:
      3411795562305994946L

    - #### Serialized Fields

      - ##### m_Cache

            Hashtable<String,String> m_Cache

        for caching long relational and string values that get processed for display.

      - ##### m_Data

            Instances m_Data

        the data

      - ##### m_IgnoreChanges

            boolean m_IgnoreChanges

        whether to ignore changes, i.e. not adding to undo history

      - ##### m_Listeners

            HashSet<TableModelListener> m_Listeners

        the listeners

      - ##### m_NotificationEnabled

            boolean m_NotificationEnabled

        whether notfication is enabled

      - ##### m_ReadOnly

            boolean m_ReadOnly

        whether the table is read-only

      - ##### m_ShowAttributeIndex

            boolean m_ShowAttributeIndex

        whether to display the attribute index in the table header.

      - ##### m_ShowAttributeWeights

            boolean m_ShowAttributeWeights

        whether to show attribute weights.

      - ##### m_ShowInstanceWeights

            boolean m_ShowInstanceWeights

        whether to show instance weights.

      - ##### m_UndoEnabled

            boolean m_UndoEnabled

        whether undo is active

      - ##### m_UndoList

            Vector<File> m_UndoList

        the undo list (contains temp. filenames)

  - ### Class weka.gui.arffviewer.ArffViewer

    class ArffViewer extends JFrame implements Serializable
    serialVersionUID:
      -7455845566922685175L

    - #### Serialized Fields

      - ##### m_MainPanel

            ArffViewerMainPanel m_MainPanel

        the main panel

  - ### Class weka.gui.arffviewer.ArffViewerMainPanel

    class ArffViewerMainPanel extends JPanel implements Serializable
    serialVersionUID:
      -8763161167586738753L

    - #### Serialized Fields

      - ##### confirmExit

            boolean confirmExit

      - ##### exitOnClose

            boolean exitOnClose

      - ##### fileChooser

            ConverterFileChooser fileChooser

      - ##### frameTitle

            String frameTitle

      - ##### height

            int height

      - ##### left

            int left

      - ##### menuBar

            JMenuBar menuBar

      - ##### menuEdit

            JMenu menuEdit

      - ##### menuEditAttributeAsClass

            JMenuItem menuEditAttributeAsClass

      - ##### menuEditClearSearch

            JMenuItem menuEditClearSearch

      - ##### menuEditCopy

            JMenuItem menuEditCopy

      - ##### menuEditDeleteAttribute

            JMenuItem menuEditDeleteAttribute

      - ##### menuEditDeleteAttributes

            JMenuItem menuEditDeleteAttributes

      - ##### menuEditDeleteInstance

            JMenuItem menuEditDeleteInstance

      - ##### menuEditDeleteInstances

            JMenuItem menuEditDeleteInstances

      - ##### menuEditRenameAttribute

            JMenuItem menuEditRenameAttribute

      - ##### menuEditSearch

            JMenuItem menuEditSearch

      - ##### menuEditSortInstances

            JMenuItem menuEditSortInstances

      - ##### menuEditUndo

            JMenuItem menuEditUndo

      - ##### menuFile

            JMenu menuFile

      - ##### menuFileClose

            JMenuItem menuFileClose

      - ##### menuFileCloseAll

            JMenuItem menuFileCloseAll

      - ##### menuFileExit

            JMenuItem menuFileExit

      - ##### menuFileOpen

            JMenuItem menuFileOpen

      - ##### menuFileProperties

            JMenuItem menuFileProperties

      - ##### menuFileSave

            JMenuItem menuFileSave

      - ##### menuFileSaveAs

            JMenuItem menuFileSaveAs

      - ##### menuView

            JMenu menuView

      - ##### menuViewAttributes

            JMenuItem menuViewAttributes

      - ##### menuViewOptimalColWidths

            JMenuItem menuViewOptimalColWidths

      - ##### menuViewValues

            JMenuItem menuViewValues

      - ##### parent

            Container parent

      - ##### tabbedPane

            JTabbedPane tabbedPane

      - ##### top

            int top

      - ##### width

            int width

- ## Package weka.gui.beans

  - ### Class weka.gui.beans.AbstractDataSink

    class AbstractDataSink extends JPanel implements Serializable
    serialVersionUID:
      3956528599473814287L

    - #### Serialized Fields

      - ##### m_listenee

            Object m_listenee

        Non null if this object is a target for any events. Provides for the simplest case when only one incomming connection is allowed. Subclasses can overide the appropriate BeanCommon methods to change this behaviour and allow multiple connections if desired

      - ##### m_visual

            BeanVisual m_visual

        Default visual for data sources

  - ### Class weka.gui.beans.AbstractDataSource

    class AbstractDataSource extends JPanel implements Serializable
    serialVersionUID:
      -4127257701890044793L

    - #### Serialized Fields

      - ##### m_bcSupport

            BeanContextChildSupport m_bcSupport

        BeanContextChild support

      - ##### m_design

            boolean m_design

        True if this bean's appearance is the design mode appearance

      - ##### m_listeners

            Vector<EventListener> m_listeners

        Objects listening for events from data sources

      - ##### m_visual

            BeanVisual m_visual

        Default visual for data sources

  - ### Class weka.gui.beans.AbstractEvaluator

    class AbstractEvaluator extends JPanel implements Serializable
    serialVersionUID:
      3983303541814121632L

    - #### Serialized Fields

      - ##### m_listenee

            Object m_listenee

      - ##### m_visual

            BeanVisual m_visual

        Default visual for evaluators

  - ### Class weka.gui.beans.AbstractTestSetProducer

    class AbstractTestSetProducer extends JPanel implements Serializable
    serialVersionUID:
      -7905764845789349839L

    - #### Serialized Fields

      - ##### m_listenee

            Object m_listenee

        non null if this object is a target for any events.

      - ##### m_listeners

            Vector<EventListener> m_listeners

        Objects listening to us

      - ##### m_visual

            BeanVisual m_visual

  - ### Class weka.gui.beans.AbstractTrainAndTestSetProducer

    class AbstractTrainAndTestSetProducer extends JPanel implements Serializable
    serialVersionUID:
      -1809339823613492037L

    - #### Serialized Fields

      - ##### m_listenee

            Object m_listenee

        non null if this object is a target for any events.

      - ##### m_testListeners

            Vector<EventListener> m_testListeners

        Objects listening for test set events

      - ##### m_trainingListeners

            Vector<EventListener> m_trainingListeners

        Objects listening for trainin set events

      - ##### m_visual

            BeanVisual m_visual

  - ### Class weka.gui.beans.AbstractTrainingSetProducer

    class AbstractTrainingSetProducer extends JPanel implements Serializable
    serialVersionUID:
      -7842746199524591125L

    - #### Serialized Fields

      - ##### m_listenee

            Object m_listenee

        non null if this object is a target for any events.

      - ##### m_listeners

            Vector<EventListener> m_listeners

        Objects listening for training set events

      - ##### m_visual

            BeanVisual m_visual

  - ### Class weka.gui.beans.Appender

    class Appender extends JPanel implements Serializable
    serialVersionUID:
      9177433051794199463L

    - #### Serialized Fields

      - ##### m_busy

            boolean m_busy

        True if we are busy

      - ##### m_dataListeners

            ArrayList<DataSourceListener> m_dataListeners

        Downstream steps listening to batch data events

      - ##### m_finishedCount

            int m_finishedCount

        Keeps track of how many incoming instance streams have finished

      - ##### m_ie

            InstanceEvent m_ie

        Instance event to use for incremental mode

      - ##### m_instanceListeners

            ArrayList<InstanceListener> m_instanceListeners

        Downstream steps listening to instance events

      - ##### m_listenees

            Map<Object,Object> m_listenees

      - ##### m_listeneeTypes

            Set<String> m_listeneeTypes

        Upstream components sending us data

      - ##### m_visual

            BeanVisual m_visual

        Default visual for data sources

  - ### Class weka.gui.beans.Associator

    class Associator extends JPanel implements Serializable
    serialVersionUID:
      -7843500322130210057L

    - #### Serialized Fields

      - ##### m_Associator

            Associator m_Associator

      - ##### m_buildThread

            Thread m_buildThread

      - ##### m_globalInfo

            String m_globalInfo

        Global info for the wrapped associator (if it exists).

      - ##### m_graphListeners

            Vector<EventListener> m_graphListeners

        Objects listening for graph events

      - ##### m_listenees

            Hashtable<String,Object> m_listenees

        Objects talking to us

      - ##### m_rulesListeners

            Vector<BatchAssociationRulesListener> m_rulesListeners

        The objects listening for batchAssociationRules events

      - ##### m_state

            int m_state

      - ##### m_textListeners

            Vector<EventListener> m_textListeners

        Objects listening for text events

      - ##### m_visual

            BeanVisual m_visual

  - ### Class weka.gui.beans.AssociatorCustomizer

    class AssociatorCustomizer extends JPanel implements Serializable
    serialVersionUID:
      5767664969353495974L

    - #### Serialized Fields

      - ##### m_AssociatorEditor

            PropertySheetPanel m_AssociatorEditor

      - ##### m_backup

            Associator m_backup

        Backup is user presses cancel

      - ##### m_dsAssociator

            Associator m_dsAssociator

      - ##### m_modifyListener

            BeanCustomizer.ModifyListener m_modifyListener

      - ##### m_parentWindow

            Window m_parentWindow

      - ##### m_pcSupport

            PropertyChangeSupport m_pcSupport

  - ### Class weka.gui.beans.AttributeSummarizer

    class AttributeSummarizer extends DataVisualizer implements Serializable
    serialVersionUID:
      -294354961169372758L

    - #### Serialized Fields

      - ##### m_activePerspective

            boolean m_activePerspective

      - ##### m_coloringIndex

            int m_coloringIndex

        Index on which to color the plots.

      - ##### m_gridWidth

            int m_gridWidth

        The number of plots horizontally in the display

      - ##### m_maxPlots

            int m_maxPlots

        The maximum number of plots to show

      - ##### m_runningAsPerspective

            boolean m_runningAsPerspective

      - ##### m_showClassCombo

            boolean m_showClassCombo

  - ### Class weka.gui.beans.AttributeSummarizerCustomizer

    class AttributeSummarizerCustomizer extends JPanel implements Serializable
    serialVersionUID:
      -6973666187676272788L

    - #### Serialized Fields

      - ##### m_dataVis

            DataVisualizer m_dataVis

      - ##### m_env

            Environment m_env

      - ##### m_height

            EnvironmentField m_height

      - ##### m_heightBack

            String m_heightBack

      - ##### m_modifyListener

            BeanCustomizer.ModifyListener m_modifyListener

      - ##### m_opts

            EnvironmentField m_opts

      - ##### m_optsBack

            String m_optsBack

      - ##### m_parent

            Window m_parent

      - ##### m_rendererCombo

            JComboBox m_rendererCombo

      - ##### m_rendererNameBack

            String m_rendererNameBack

      - ##### m_width

            EnvironmentField m_width

      - ##### m_widthBack

            String m_widthBack

      - ##### m_xAxis

            EnvironmentField m_xAxis

      - ##### m_xAxisBack

            String m_xAxisBack

  - ### Class weka.gui.beans.BatchAssociationRulesEvent

    class BatchAssociationRulesEvent extends EventObject implements Serializable
    serialVersionUID:
      6332614648885439492L

    - #### Serialized Fields

      - ##### m_rules

            AssociationRules m_rules

        The encapsulated rules

  - ### Class weka.gui.beans.BatchClassifierEvent

    class BatchClassifierEvent extends EventObject implements Serializable
    serialVersionUID:
      878097199815991084L

    - #### Serialized Fields

      - ##### m_classifier

            Classifier m_classifier

        The classifier

      - ##### m_eventLabel

            String m_eventLabel

        Label for this event

      - ##### m_groupIdentifier

            long m_groupIdentifier

        An identifier that can be used to group all related runs/sets together.

      - ##### m_maxRunNumber

            int m_maxRunNumber

        The maximum number of runs

      - ##### m_maxSetNumber

            int m_maxSetNumber

        The last set number for this series

      - ##### m_runNumber

            int m_runNumber

        The run number that this classifier was generated for

      - ##### m_setNumber

            int m_setNumber

        The set number for the test set

      - ##### m_testSet

            DataSetEvent m_testSet

        Instances that can be used for testing the classifier

      - ##### m_trainSet

            DataSetEvent m_trainSet

        Instances that were used to train the classifier (may be null if not available)

  - ### Class weka.gui.beans.BatchClustererEvent

    class BatchClustererEvent extends EventObject implements Serializable
    serialVersionUID:
      7268777944939129714L

    - #### Serialized Fields

      - ##### m_clusterer

            Clusterer m_clusterer

        The clusterer

      - ##### m_maxSetNumber

            int m_maxSetNumber

        The last set number for this series

      - ##### m_setNumber

            int m_setNumber

        The set number for the test set

      - ##### m_testOrTrain

            int m_testOrTrain

        Indicates if m_testSet is a training or a test set. 0 for test, >0 for training

      - ##### m_testSet

            DataSetEvent m_testSet

        Training or Test Instances

  - ### Class weka.gui.beans.BeanConnection

    class BeanConnection extends Object implements Serializable
    serialVersionUID:
      8804264241791332064L

    - #### Serialized Fields

      - ##### m_eventName

            String m_eventName

        The name of the event for this connection

      - ##### m_hidden

            boolean m_hidden

      - ##### m_source

            BeanInstance m_source

      - ##### m_target

            BeanInstance m_target

  - ### Class weka.gui.beans.BeanInstance

    class BeanInstance extends Object implements Serializable
    serialVersionUID:
      -7575653109025406342L

    - #### Serialized Fields

      - ##### m_bean

            Object m_bean

        Holds the bean encapsulated in this instance

      - ##### m_x

            int m_x

      - ##### m_y

            int m_y

  - ### Class weka.gui.beans.BeansProperties

    class BeansProperties extends Object implements Serializable
    serialVersionUID:
      7183413615090695785L

  - ### Class weka.gui.beans.BeanVisual

    class BeanVisual extends JPanel implements Serializable
    serialVersionUID:
      -6677473561687129614L

    - #### Serialization Methods

      - ##### readObject

        private void readObject(ObjectInputStream ois) throws IOException, ClassNotFoundException
        Overides default read object in order to reload icons. This is necessary because for some strange reason animated gifs stop being animated after being serialized/deserialized.
        Parameters:
          `ois` - an `ObjectInputStream` value
        Throws:
          `IOException` - if an error occurs
          `ClassNotFoundException` - if an error occurs

    - #### Serialized Fields

      - ##### m_animatedIconPath

            String m_animatedIconPath

        Holds name (including path) of the animated icon

      - ##### m_connectorColor

            Color m_connectorColor

      - ##### m_displayConnectors

            boolean m_displayConnectors

      - ##### m_iconPath

            String m_iconPath

        Holds name (including path) of the static icon

      - ##### m_pcs

            PropertyChangeSupport m_pcs

        Container for the icon

      - ##### m_visualLabel

            JLabel m_visualLabel

      - ##### m_visualName

            String m_visualName

        Name for the bean

  - ### Class weka.gui.beans.ChartEvent

    class ChartEvent extends EventObject implements Serializable
    serialVersionUID:
      7812460715499569390L

    - #### Serialized Fields

      - ##### m_dataPoint

            double[] m_dataPoint

        Y values of the data points

      - ##### m_legendText

            Vector<String> m_legendText

      - ##### m_max

            double m_max

      - ##### m_min

            double m_min

      - ##### m_reset

            boolean m_reset

  - ### Class weka.gui.beans.ClassAssigner

    class ClassAssigner extends JPanel implements Serializable
    serialVersionUID:
      4011131665025817924L

    - #### Serialized Fields

      - ##### m_classColumn

            String m_classColumn

      - ##### m_connectedFormat

            Instances m_connectedFormat

        format of instances for current incoming connection (if any)

      - ##### m_dataFormatListeners

            Vector<DataFormatListener> m_dataFormatListeners

      - ##### m_dataListeners

            Vector<DataSourceListener> m_dataListeners

      - ##### m_dataProvider

            Object m_dataProvider

      - ##### m_instanceListeners

            Vector<InstanceListener> m_instanceListeners

      - ##### m_instanceProvider

            Object m_instanceProvider

      - ##### m_testListeners

            Vector<TestSetListener> m_testListeners

      - ##### m_testProvider

            Object m_testProvider

      - ##### m_trainingListeners

            Vector<TrainingSetListener> m_trainingListeners

      - ##### m_trainingProvider

            Object m_trainingProvider

      - ##### m_visual

            BeanVisual m_visual

  - ### Class weka.gui.beans.ClassAssignerCustomizer

    class ClassAssignerCustomizer extends JPanel implements Serializable
    serialVersionUID:
      476539385765301907L

    - #### Serialized Fields

      - ##### m_displayColNames

            boolean m_displayColNames

  - ### Class weka.gui.beans.Classifier

    class Classifier extends JPanel implements Serializable
    serialVersionUID:
      659603893917736008L

    - #### Serialized Fields

      - ##### m_batchClassifierListeners

            Vector<BatchClassifierListener> m_batchClassifierListeners

        Objects listening for batch classifier events

      - ##### m_binaryFilter

            FileFilter m_binaryFilter

      - ##### m_block

            boolean m_block

        True if we should block rather reject until all processing has been completed.

      - ##### m_Classifier

            Classifier m_Classifier

      - ##### m_ClassifierTemplate

            Classifier m_ClassifierTemplate

        Template used for creating copies when building in parallel

      - ##### m_executionSlots

            int m_executionSlots

        Number of threads to use to train models with

      - ##### m_globalInfo

            String m_globalInfo

        Global info for the wrapped classifier (if it exists).

      - ##### m_graphListeners

            Vector<GraphListener> m_graphListeners

        Objects listening for graph events

      - ##### m_ie

            IncrementalClassifierEvent m_ie

      - ##### m_incrementalClassifierListeners

            Vector<IncrementalClassifierListener> m_incrementalClassifierListeners

        Objects listening for incremental classifier events

      - ##### m_incrementalEvent

            InstanceEvent m_incrementalEvent

        Event to handle when processing incremental updates

      - ##### m_KOMLFilter

            FileFilter m_KOMLFilter

      - ##### m_listenees

            HashMap<String,List<Object>> m_listenees

        Objects talking to us. String connection event key, 2 element list containing source and count

      - ##### m_loadModelFileName

            String m_loadModelFileName

        Optional file to load a pre-trained model to score with (batch, or to score and update (incremental) in the case of testSet only (batch) or instance (incremental) connections

      - ##### m_oldText

            String m_oldText

        Holds original icon label text

      - ##### m_reject

            boolean m_reject

        true if we should reject any further training data sets, until all processing has been finished, once we've received the last fold of the last run.

      - ##### m_resetIncrementalClassifier

            boolean m_resetIncrementalClassifier

        If the classifier is an incremental classifier, should we reset it (i.e. call buildClassifier()) and discard any previously learned model before processing the first instance in the stream. Note that this happens automatically if the incoming instance structure does not match that (if any) that the classifier was trained with previously.

      - ##### m_state

            int m_state

      - ##### m_textListeners

            Vector<TextListener> m_textListeners

        Objects listening for text events

      - ##### m_trainingSet

            Instances m_trainingSet

        Holds training instances for batch training. Not transient because header is retained for validating any instance events that this classifier might be asked to predict in the future.

      - ##### m_updateIncrementalClassifier

            boolean m_updateIncrementalClassifier

        If the classifier is an incremental classifier, should we update it (ie train it on incoming instances). This makes it possible incrementally test on a separate stream of instances without updating the classifier, or mix batch training/testing with incremental training/testing

      - ##### m_visual

            BeanVisual m_visual

      - ##### m_XStreamFilter

            FileFilter m_XStreamFilter

  - ### Class weka.gui.beans.Classifier.TrainingTask

    class TrainingTask extends Object implements Serializable
    serialVersionUID:
      -7918128680624169641L

    - #### Serialized Fields

      - ##### m_maxRunNum

            int m_maxRunNum

      - ##### m_maxSetNum

            int m_maxSetNum

      - ##### m_runNum

            int m_runNum

      - ##### m_setNum

            int m_setNum

      - ##### m_taskInfo

            TaskStatusInfo m_taskInfo

      - ##### m_train

            Instances m_train

  - ### Class weka.gui.beans.ClassifierCustomizer

    class ClassifierCustomizer extends JPanel implements Serializable
    serialVersionUID:
      -6688000820160821429L

    - #### Serialized Fields

      - ##### m_backup

            Classifier m_backup

        Copy of the current classifier in case cancel is selected

      - ##### m_blockOnLastFold

            JCheckBox m_blockOnLastFold

      - ##### m_ClassifierEditor

            PropertySheetPanel m_ClassifierEditor

      - ##### m_dsClassifier

            Classifier m_dsClassifier

      - ##### m_env

            Environment m_env

      - ##### m_executionSlotsLabel

            JLabel m_executionSlotsLabel

      - ##### m_executionSlotsPanel

            JPanel m_executionSlotsPanel

      - ##### m_executionSlotsText

            JTextField m_executionSlotsText

      - ##### m_holderPanel

            JPanel m_holderPanel

      - ##### m_incrementalPanel

            JPanel m_incrementalPanel

      - ##### m_loadModelField

            FileEnvironmentField m_loadModelField

      - ##### m_modifyListener

            BeanCustomizer.ModifyListener m_modifyListener

        Listener that wants to know the the modified status of the object that we're customizing

      - ##### m_panelVisible

            boolean m_panelVisible

      - ##### m_parentWindow

            Window m_parentWindow

      - ##### m_pcSupport

            PropertyChangeSupport m_pcSupport

      - ##### m_resetIncrementalClassifier

            JCheckBox m_resetIncrementalClassifier

      - ##### m_updateIncrementalClassifier

            JCheckBox m_updateIncrementalClassifier

  - ### Class weka.gui.beans.ClassifierPerformanceEvaluator

    class ClassifierPerformanceEvaluator extends AbstractEvaluator implements Serializable
    serialVersionUID:
      -3511801418192148690L

    - #### Serialized Fields

      - ##### m_errorPlotPointSizeProportionalToMargin

            boolean m_errorPlotPointSizeProportionalToMargin

      - ##### m_executionSlots

            int m_executionSlots

        Number of threads to use to train models with

      - ##### m_metricsList

            List<String> m_metricsList

      - ##### m_selectedEvalMetrics

            String m_selectedEvalMetrics

        Evaluation metrics to output

      - ##### m_textListeners

            Vector<TextListener> m_textListeners

      - ##### m_thresholdListeners

            Vector<ThresholdDataListener> m_thresholdListeners

      - ##### m_visualizableErrorListeners

            Vector<VisualizableErrorListener> m_visualizableErrorListeners

  - ### Class weka.gui.beans.ClassifierPerformanceEvaluator.AggregateableClassifierErrorsPlotInstances

    class AggregateableClassifierErrorsPlotInstances extends ClassifierErrorsPlotInstances implements Serializable
    serialVersionUID:
      2012744784036684168L

  - ### Class weka.gui.beans.ClassifierPerformanceEvaluator.EvaluationTask

    class EvaluationTask extends Object implements Serializable
    serialVersionUID:
      -8939077467030259059L

    - #### Serialized Fields

      - ##### m_classifier

            Classifier m_classifier

      - ##### m_evalLabel

            String m_evalLabel

      - ##### m_maxSetNum

            int m_maxSetNum

      - ##### m_setNum

            int m_setNum

      - ##### m_stopped

            boolean m_stopped

      - ##### m_testData

            Instances m_testData

      - ##### m_trainData

            Instances m_trainData

  - ### Class weka.gui.beans.ClassifierPerformanceEvaluatorCustomizer

    class ClassifierPerformanceEvaluatorCustomizer extends JPanel implements Serializable
    serialVersionUID:
      -1055460295546483853L

    - #### Serialized Fields

      - ##### m_cpe

            ClassifierPerformanceEvaluator m_cpe

      - ##### m_evalMetricsBut

            JButton m_evalMetricsBut

      - ##### m_evaluationMetrics

            List<String> m_evaluationMetrics

      - ##### m_executionSlotsBackup

            int m_executionSlotsBackup

      - ##### m_modifyListener

            BeanCustomizer.ModifyListener m_modifyListener

      - ##### m_parent

            Window m_parent

      - ##### m_pcSupport

            PropertyChangeSupport m_pcSupport

      - ##### m_splitEditor

            PropertySheetPanel m_splitEditor

  - ### Class weka.gui.beans.ClassValuePicker

    class ClassValuePicker extends JPanel implements Serializable
    serialVersionUID:
      -1196143276710882989L

    - #### Serialized Fields

      - ##### m_classValue

            String m_classValue

        the class value considered to be the positive class

      - ##### m_connectedFormat

            Instances m_connectedFormat

        format of instances for the current incoming connection (if any)

      - ##### m_dataFormatListeners

            Vector<DataFormatListener> m_dataFormatListeners

      - ##### m_dataListeners

            Vector<DataSourceListener> m_dataListeners

      - ##### m_dataProvider

            Object m_dataProvider

      - ##### m_visual

            BeanVisual m_visual

  - ### Class weka.gui.beans.ClassValuePickerCustomizer

    class ClassValuePickerCustomizer extends JPanel implements Serializable
    serialVersionUID:
      8213423053861600469L

    - #### Serialized Fields

      - ##### m_backup

            String m_backup

      - ##### m_ClassValueCombo

            JComboBox m_ClassValueCombo

      - ##### m_classValuePicker

            ClassValuePicker m_classValuePicker

      - ##### m_displayValNames

            boolean m_displayValNames

      - ##### m_holderP

            JPanel m_holderP

      - ##### m_messageLabel

            JLabel m_messageLabel

      - ##### m_modified

            boolean m_modified

      - ##### m_modifyListener

            BeanCustomizer.ModifyListener m_modifyListener

      - ##### m_parent

            Window m_parent

      - ##### m_pcSupport

            PropertyChangeSupport m_pcSupport

      - ##### m_textBoxEntryMode

            boolean m_textBoxEntryMode

      - ##### m_valueTextBox

            JTextField m_valueTextBox

  - ### Class weka.gui.beans.Clusterer

    class Clusterer extends JPanel implements Serializable
    serialVersionUID:
      7729795159836843810L

    - #### Serialized Fields

      - ##### m_batchClustererListeners

            Vector<BatchClustererListener> m_batchClustererListeners

        Objects listening for batch clusterer events

      - ##### m_buildThread

            Thread m_buildThread

      - ##### m_Clusterer

            Clusterer m_Clusterer

      - ##### m_dummy

            Double m_dummy

      - ##### m_globalInfo

            String m_globalInfo

        Global info for the wrapped classifier (if it exists).

      - ##### m_graphListeners

            Vector<GraphListener> m_graphListeners

        Objects listening for graph events

      - ##### m_listenees

            Hashtable<String,Object> m_listenees

        Objects talking to us

      - ##### m_state

            int m_state

      - ##### m_textListeners

            Vector<TextListener> m_textListeners

        Objects listening for text events

      - ##### m_trainingSet

            Instances m_trainingSet

        Holds training instances for batch training.

      - ##### m_visual

            BeanVisual m_visual

  - ### Class weka.gui.beans.ClustererCustomizer

    class ClustererCustomizer extends JPanel implements Serializable
    serialVersionUID:
      -2035688458149534161L

    - #### Serialized Fields

      - ##### m_backup

            Clusterer m_backup

        Backup if the user presses cancel

      - ##### m_ClustererEditor

            PropertySheetPanel m_ClustererEditor

      - ##### m_dsClusterer

            Clusterer m_dsClusterer

      - ##### m_modifyListener

            BeanCustomizer.ModifyListener m_modifyListener

      - ##### m_parentWindow

            Window m_parentWindow

      - ##### m_pcSupport

            PropertyChangeSupport m_pcSupport

  - ### Class weka.gui.beans.ClustererPerformanceEvaluator

    class ClustererPerformanceEvaluator extends AbstractEvaluator implements Serializable
    serialVersionUID:
      8041163601333978584L

    - #### Serialized Fields

      - ##### m_textListeners

            Vector<TextListener> m_textListeners

  - ### Class weka.gui.beans.ConfigurationEvent

    class ConfigurationEvent extends EventObject implements Serializable
    serialVersionUID:
      5433562112093780868L

  - ### Class weka.gui.beans.CostBenefitAnalysis

    class CostBenefitAnalysis extends JPanel implements Serializable
    serialVersionUID:
      8647471654613320469L

    - #### Serialized Fields

      - ##### m_bcSupport

            BeanContextChildSupport m_bcSupport

        BeanContextChild support

      - ##### m_design

            boolean m_design

        True if this bean's appearance is the design mode appearance

      - ##### m_framePoppedUp

            boolean m_framePoppedUp

      - ##### m_headlessEvents

            List<EventObject> m_headlessEvents

      - ##### m_listenee

            Object m_listenee

        The object sending us data (we allow only one connection at any one time)

      - ##### m_visual

            BeanVisual m_visual

  - ### Class weka.gui.beans.CostBenefitAnalysis.AnalysisPanel

    class AnalysisPanel extends JPanel implements Serializable
    serialVersionUID:
      5364871945448769003L

    - #### Serialized Fields

      - ##### m_benefitR

            JRadioButton m_benefitR

      - ##### m_classAttribute

            Attribute m_classAttribute

        The class attribute from the data that was used to generate the threshold curve

      - ##### m_classificationAccV

            JLabel m_classificationAccV

        Classification accuracy

      - ##### m_conf_aa

            weka.gui.beans.CostBenefitAnalysis.AnalysisPanel.ConfusionCell m_conf_aa

      - ##### m_conf_ab

            weka.gui.beans.CostBenefitAnalysis.AnalysisPanel.ConfusionCell m_conf_ab

      - ##### m_conf_actualA

            JLabel m_conf_actualA

      - ##### m_conf_actualB

            JLabel m_conf_actualB

      - ##### m_conf_ba

            weka.gui.beans.CostBenefitAnalysis.AnalysisPanel.ConfusionCell m_conf_ba

      - ##### m_conf_bb

            weka.gui.beans.CostBenefitAnalysis.AnalysisPanel.ConfusionCell m_conf_bb

      - ##### m_conf_predictedA

            JLabel m_conf_predictedA

      - ##### m_conf_predictedB

            JLabel m_conf_predictedB

      - ##### m_cost_aa

            JTextField m_cost_aa

      - ##### m_cost_ab

            JTextField m_cost_ab

      - ##### m_cost_actualA

            JLabel m_cost_actualA

      - ##### m_cost_actualB

            JLabel m_cost_actualB

      - ##### m_cost_ba

            JTextField m_cost_ba

      - ##### m_cost_bb

            JTextField m_cost_bb

      - ##### m_cost_predictedA

            JLabel m_cost_predictedA

      - ##### m_cost_predictedB

            JLabel m_cost_predictedB

      - ##### m_costBenefit

            PlotData2D m_costBenefit

        Data for the cost/benefit curve

      - ##### m_costBenefitL

            JLabel m_costBenefitL

      - ##### m_costBenefitPanel

            VisualizePanel m_costBenefitPanel

        Displays the cost/benefit (profit/loss) graph

      - ##### m_costBenefitV

            JLabel m_costBenefitV

      - ##### m_costR

            JRadioButton m_costR

      - ##### m_fnPrevious

            double m_fnPrevious

      - ##### m_fpPrevious

            double m_fpPrevious

      - ##### m_gainV

            JLabel m_gainV

      - ##### m_masterPlot

            PlotData2D m_masterPlot

        Data for the threshold curve

      - ##### m_maximizeCB

            JButton m_maximizeCB

      - ##### m_minimizeCB

            JButton m_minimizeCB

      - ##### m_originalPopSize

            int m_originalPopSize

      - ##### m_percOfTarget

            JRadioButton m_percOfTarget

      - ##### m_percOfTargetLab

            JLabel m_percOfTargetLab

      - ##### m_percPop

            JRadioButton m_percPop

      - ##### m_percPopLab

            JLabel m_percPopLab

      - ##### m_performancePanel

            VisualizePanel m_performancePanel

        Displays the performance graphs(s)

      - ##### m_previousShapeIndex

            int m_previousShapeIndex

        The index of the previous plotted point that was highlighted

      - ##### m_randomV

            JLabel m_randomV

      - ##### m_shapeSizes

            int[] m_shapeSizes

        The size of the points being plotted

      - ##### m_threshold

            JRadioButton m_threshold

      - ##### m_thresholdLab

            JLabel m_thresholdLab

      - ##### m_thresholdSlider

            JSlider m_thresholdSlider

        The slider for adjusting the threshold

      - ##### m_tnPrevious

            double m_tnPrevious

      - ##### m_totalPopField

            JTextField m_totalPopField

        Population text field

      - ##### m_totalPopPrevious

            int m_totalPopPrevious

      - ##### m_tpPrevious

            double m_tpPrevious

  - ### Class weka.gui.beans.CostBenefitAnalysis.AnalysisPanel.ConfusionCell

    class ConfusionCell extends JPanel implements Serializable
    serialVersionUID:
      6148640235434494767L

    - #### Serialized Fields

      - ##### m_conf_cell

            JLabel m_conf_cell

      - ##### m_conf_perc

            JLabel m_conf_perc

      - ##### m_percentage

            double m_percentage

      - ##### m_percentageP

            JPanel m_percentageP

  - ### Class weka.gui.beans.CrossValidationFoldMaker

    class CrossValidationFoldMaker extends AbstractTrainAndTestSetProducer implements Serializable
    serialVersionUID:
      -6350179298851891512L

    - #### Serialized Fields

      - ##### m_dataProvider

            boolean m_dataProvider

      - ##### m_numFolds

            int m_numFolds

      - ##### m_preserveOrder

            boolean m_preserveOrder

      - ##### m_randomSeed

            int m_randomSeed

      - ##### m_testProvider

            boolean m_testProvider

      - ##### m_trainingProvider

            boolean m_trainingProvider

  - ### Class weka.gui.beans.CrossValidationFoldMakerCustomizer

    class CrossValidationFoldMakerCustomizer extends JPanel implements Serializable
    serialVersionUID:
      1229878140258668581L

    - #### Serialized Fields

      - ##### m_cvEditor

            PropertySheetPanel m_cvEditor

      - ##### m_cvMaker

            CrossValidationFoldMaker m_cvMaker

      - ##### m_foldsBackup

            int m_foldsBackup

      - ##### m_modifyListener

            BeanCustomizer.ModifyListener m_modifyListener

      - ##### m_orderBackup

            boolean m_orderBackup

      - ##### m_parent

            Window m_parent

      - ##### m_pcSupport

            PropertyChangeSupport m_pcSupport

      - ##### m_seedBackup

            int m_seedBackup

  - ### Class weka.gui.beans.DataSetEvent

    class DataSetEvent extends EventObject implements Serializable
    serialVersionUID:
      -5111218447577318057L

    - #### Serialized Fields

      - ##### m_dataSet

            Instances m_dataSet

      - ##### m_structureOnly

            boolean m_structureOnly

  - ### Class weka.gui.beans.DataVisualizer

    class DataVisualizer extends JPanel implements Serializable
    serialVersionUID:
      1949062132560159028L

    - #### Serialized Fields

      - ##### m_additionalOptions

            String m_additionalOptions

        Additional options for the offscreen renderer

      - ##### m_bcSupport

            BeanContextChildSupport m_bcSupport

        BeanContextChild support

      - ##### m_dataSetListeners

            Vector<DataSourceListener> m_dataSetListeners

        Objects listening for data set events

      - ##### m_design

            boolean m_design

        True if this bean's appearance is the design mode appearance

      - ##### m_framePoppedUp

            boolean m_framePoppedUp

      - ##### m_headlessEvents

            List<EventObject> m_headlessEvents

        Events received and stored during headless execution

      - ##### m_height

            String m_height

        Height of offscreen plots

      - ##### m_imageListeners

            ArrayList<ImageListener> m_imageListeners

      - ##### m_listenees

            List<Object> m_listenees

      - ##### m_offscreenRendererName

            String m_offscreenRendererName

        Name of the renderer to use for offscreen chart rendering

      - ##### m_visPanel

            VisualizePanel m_visPanel

      - ##### m_visual

            BeanVisual m_visual

      - ##### m_width

            String m_width

        Width of offscreen plots

      - ##### m_xAxis

            String m_xAxis

        The name of the attribute to use for the x-axis of offscreen plots. If left empty, False Positive Rate is used for threshold curves

      - ##### m_yAxis

            String m_yAxis

        The name of the attribute to use for the y-axis of offscreen plots. If left empty, True Positive Rate is used for threshold curves

  - ### Class weka.gui.beans.DataVisualizerCustomizer

    class DataVisualizerCustomizer extends JPanel implements Serializable
    serialVersionUID:
      27802741348090392L

    - #### Serialized Fields

      - ##### m_dataVis

            DataVisualizer m_dataVis

      - ##### m_env

            Environment m_env

      - ##### m_height

            EnvironmentField m_height

      - ##### m_heightBack

            String m_heightBack

      - ##### m_modifyListener

            BeanCustomizer.ModifyListener m_modifyListener

      - ##### m_opts

            EnvironmentField m_opts

      - ##### m_optsBack

            String m_optsBack

      - ##### m_parent

            Window m_parent

      - ##### m_rendererCombo

            JComboBox m_rendererCombo

      - ##### m_rendererNameBack

            String m_rendererNameBack

      - ##### m_width

            EnvironmentField m_width

      - ##### m_widthBack

            String m_widthBack

      - ##### m_xAxis

            EnvironmentField m_xAxis

      - ##### m_xAxisBack

            String m_xAxisBack

      - ##### m_yAxis

            EnvironmentField m_yAxis

      - ##### m_yAxisBack

            String m_yAxisBack

  - ### Class weka.gui.beans.EnvironmentField

    class EnvironmentField extends JPanel implements Serializable
    serialVersionUID:
      -3125404573324734121L

    - #### Serialized Fields

      - ##### m_combo

            JComboBox m_combo

        Deprecated.
        The combo box

      - ##### m_currentCaretPos

            int m_currentCaretPos

        Deprecated.

      - ##### m_currentContents

            String m_currentContents

        Deprecated.

      - ##### m_env

            Environment m_env

        Deprecated.
        The current environment variables

      - ##### m_firstCaretPos

            int m_firstCaretPos

        Deprecated.

      - ##### m_label

            JLabel m_label

        Deprecated.
        The label for the widget

      - ##### m_previousCaretPos

            int m_previousCaretPos

        Deprecated.

      - ##### m_support

            PropertyChangeSupport m_support

        Deprecated.

  - ### Class weka.gui.beans.EnvironmentField.WideComboBox

    class WideComboBox extends JComboBox implements Serializable
    serialVersionUID:
      -6512065375459733517L

    - #### Serialized Fields

      - ##### m_layingOut

            boolean m_layingOut

  - ### Class weka.gui.beans.FileEnvironmentField

    class FileEnvironmentField extends EnvironmentField implements Serializable
    serialVersionUID:
      -233731548086207652L

    - #### Serialized Fields

      - ##### m_browseBut

            JButton m_browseBut

        Deprecated.
        The button to pop up the file dialog

      - ##### m_fileEditor

            FileEditor m_fileEditor

        Deprecated.
        File editor component

      - ##### m_fileEditorDialog

            PropertyDialog m_fileEditorDialog

        Deprecated.
        Dialog to hold the file editor

  - ### Class weka.gui.beans.Filter

    class Filter extends JPanel implements Serializable
    serialVersionUID:
      8249759470189439321L

    - #### Serialized Fields

      - ##### m_dataListeners

            Vector<DataSourceListener> m_dataListeners

        Objects listening for data set events

      - ##### m_Filter

            Filter m_Filter

        The filter to use.

      - ##### m_globalInfo

            String m_globalInfo

        Global info for the wrapped filter (if it exists).

      - ##### m_ie

            InstanceEvent m_ie

        Instance event object for passing on filtered instance streams

      - ##### m_instanceListeners

            Vector<InstanceListener> m_instanceListeners

        Objects listening for instance events

      - ##### m_listenees

            Hashtable<String,Object> m_listenees

        Objects talking to us

      - ##### m_state

            int m_state

      - ##### m_structurePassedOn

            boolean m_structurePassedOn

      - ##### m_testListeners

            Vector<TestSetListener> m_testListeners

        Objects listening for test set events

      - ##### m_trainingListeners

            Vector<TrainingSetListener> m_trainingListeners

        Objects listening for training set events

      - ##### m_visual

            BeanVisual m_visual

  - ### Class weka.gui.beans.FilterCustomizer

    class FilterCustomizer extends JPanel implements Serializable
    serialVersionUID:
      2049895469240109738L

    - #### Serialized Fields

      - ##### m_backup

            Filter m_backup

        Backup if user presses cancel

      - ##### m_filter

            Filter m_filter

      - ##### m_filterEditor

            PropertySheetPanel m_filterEditor

      - ##### m_modifyListener

            BeanCustomizer.ModifyListener m_modifyListener

      - ##### m_parentWindow

            Window m_parentWindow

      - ##### m_pcSupport

            PropertyChangeSupport m_pcSupport

  - ### Class weka.gui.beans.FlowByExpression

    class FlowByExpression extends JPanel implements Serializable
    serialVersionUID:
      2492050246494259885L

    - #### Serialized Fields

      - ##### m_connectedFormat

            Instances m_connectedFormat

        format of instances for current incoming connection (if any)

      - ##### m_connectionType

            String m_connectionType

        The type of the incoming connection

      - ##### m_customNameOfFalseStep

            String m_customNameOfFalseStep

        Name of the step to receive instances that evaluate to false via the expression

      - ##### m_customNameOfTrueStep

            String m_customNameOfTrueStep

        Name of the step to receive instances that evaluate to true via the expression

      - ##### m_downstream

            Object[] m_downstream

        The one or two downstream steps - one for instances that match the expression and the other for instances that don't

      - ##### m_expressionString

            String m_expressionString

        The expression tree to use in internal textual format

      - ##### m_ie

            InstanceEvent m_ie

        Instance event to use

      - ##### m_indexOfFalseStep

            int m_indexOfFalseStep

      - ##### m_indexOfTrueStep

            int m_indexOfTrueStep

      - ##### m_listenee

            Object m_listenee

        Component talking to us

      - ##### m_root

            weka.gui.beans.FlowByExpression.ExpressionNode m_root

        The root of the expression tree

      - ##### m_visual

            BeanVisual m_visual

        Default visual filters

  - ### Class weka.gui.beans.FlowByExpression.BracketNode

    class BracketNode extends weka.gui.beans.FlowByExpression.ExpressionNode implements Serializable
    serialVersionUID:
      8732159083173001115L

    - #### Serialized Fields

      - ##### m_children

            List<weka.gui.beans.FlowByExpression.ExpressionNode> m_children

  - ### Class weka.gui.beans.FlowByExpression.ExpressionClause

    class ExpressionClause extends weka.gui.beans.FlowByExpression.ExpressionNode implements Serializable
    serialVersionUID:
      2754006654981248325L

    - #### Serialized Fields

      - ##### m_lhsAttIndex

            int m_lhsAttIndex

        The index of the lhs attribute

      - ##### m_lhsAttributeName

            String m_lhsAttributeName

        The name of the lhs attribute

      - ##### m_numericOperand

            double m_numericOperand

        The rhs operand (if constant and is a number )

      - ##### m_operator

            FlowByExpression.ExpressionClause.ExpressionType m_operator

        The operator for this expression

      - ##### m_regexPattern

            Pattern m_regexPattern

        the compiled regex pattern (if the operator is REGEX)

      - ##### m_resolvedLhsName

            String m_resolvedLhsName

        The name of the lhs attribute after resolving variables

      - ##### m_resolvedRhsOperand

            String m_resolvedRhsOperand

        The rhs operand after resolving variables

      - ##### m_rhsAttIndex

            int m_rhsAttIndex

        index of the rhs if it is an attribute

      - ##### m_rhsIsAttribute

            boolean m_rhsIsAttribute

        True if the rhs operand is an attribute

      - ##### m_rhsOperand

            String m_rhsOperand

        The rhs operand (constant value or attribute name)

  - ### Class weka.gui.beans.FlowByExpression.ExpressionNode

    class ExpressionNode extends Object implements Serializable
    serialVersionUID:
      -8427857202322768762L

    - #### Serialized Fields

      - ##### m_isAnOr

            boolean m_isAnOr

        boolean operator for combining with result so far

      - ##### m_isNegated

            boolean m_isNegated

        is this node negated?

      - ##### m_showAndOr

            boolean m_showAndOr

        Whether to show the combination operator in the textual representation

  - ### Class weka.gui.beans.FlowByExpressionCustomizer

    class FlowByExpressionCustomizer extends JPanel implements Serializable
    serialVersionUID:
      -3574741335754017794L

    - #### Serialized Fields

      - ##### m_addBracketNode

            JButton m_addBracketNode

      - ##### m_addExpressionNode

            JButton m_addExpressionNode

      - ##### m_andOr

            JButton m_andOr

      - ##### m_deleteNode

            JButton m_deleteNode

      - ##### m_env

            Environment m_env

      - ##### m_expression

            FlowByExpression m_expression

      - ##### m_expressionLab

            JLabel m_expressionLab

      - ##### m_expressionTree

            JTree m_expressionTree

      - ##### m_falseData

            JComboBox m_falseData

      - ##### m_lhsField

            JComboBox m_lhsField

      - ##### m_modifyL

            BeanCustomizer.ModifyListener m_modifyL

      - ##### m_operatorCombo

            JComboBox m_operatorCombo

      - ##### m_parent

            Window m_parent

      - ##### m_rhsField

            JComboBox m_rhsField

      - ##### m_rhsIsAttribute

            JCheckBox m_rhsIsAttribute

      - ##### m_tempEditor

            PropertySheetPanel m_tempEditor

      - ##### m_toggleNegation

            JButton m_toggleNegation

      - ##### m_treeRoot

            DefaultMutableTreeNode m_treeRoot

      - ##### m_trueData

            JComboBox m_trueData

  - ### Class weka.gui.beans.GraphEvent

    class GraphEvent extends EventObject implements Serializable
    serialVersionUID:
      2099494034652519986L

    - #### Serialized Fields

      - ##### m_graphString

            String m_graphString

      - ##### m_graphTitle

            String m_graphTitle

      - ##### m_graphType

            int m_graphType

  - ### Class weka.gui.beans.GraphViewer

    class GraphViewer extends JPanel implements Serializable
    serialVersionUID:
      -5183121972114900617L

    - #### Serialized Fields

      - ##### m_bcSupport

            BeanContextChildSupport m_bcSupport

        BeanContextChild support

      - ##### m_design

            boolean m_design

        True if this bean's appearance is the design mode appearance

      - ##### m_visual

            BeanVisual m_visual

  - ### Class weka.gui.beans.ImageEvent

    class ImageEvent extends EventObject implements Serializable
    serialVersionUID:
      -8126533743311557969L

    - #### Serialized Fields

      - ##### m_image

            BufferedImage m_image

        The image

      - ##### m_imageName

            String m_imageName

        The name of the image

  - ### Class weka.gui.beans.ImageSaver

    class ImageSaver extends JPanel implements Serializable
    serialVersionUID:
      -641438159956934314L

    - #### Serialized Fields

      - ##### m_fileName

            String m_fileName

        The file to save to

      - ##### m_listenee

            Object m_listenee

        Non null if this object is a target for any events. Provides for the simplest case when only one incomming connection is allowed.

      - ##### m_visual

            BeanVisual m_visual

        Default visual for data sources

  - ### Class weka.gui.beans.ImageSaverCustomizer

    class ImageSaverCustomizer extends JPanel implements Serializable
    serialVersionUID:
      5215477777077643368L

    - #### Serialized Fields

      - ##### m_env

            Environment m_env

      - ##### m_fileBackup

            String m_fileBackup

      - ##### m_fileEditor

            FileEnvironmentField m_fileEditor

      - ##### m_imageSaver

            ImageSaver m_imageSaver

      - ##### m_modifyListener

            BeanCustomizer.ModifyListener m_modifyListener

      - ##### m_parent

            Window m_parent

  - ### Class weka.gui.beans.ImageViewer

    class ImageViewer extends JPanel implements Serializable
    serialVersionUID:
      7976930810628389750L

    - #### Serialized Fields

      - ##### m_history

            ResultHistoryPanel m_history

        Keeps a history of the images received

      - ##### m_plotter

            weka.gui.beans.ImageViewer.ImageDisplayer m_plotter

        Panel for displaying the image

      - ##### m_visual

            BeanVisual m_visual

        Default visual for data sources

  - ### Class weka.gui.beans.IncrementalClassifierEvaluator

    class IncrementalClassifierEvaluator extends AbstractEvaluator implements Serializable
    serialVersionUID:
      -3105419818939541291L

    - #### Serialized Fields

      - ##### m_ce

            ChartEvent m_ce

      - ##### m_dataLegend

            Vector<String> m_dataLegend

      - ##### m_dataPoint

            double[] m_dataPoint

      - ##### m_instanceCount

            int m_instanceCount

      - ##### m_listeners

            Vector<ChartListener> m_listeners

      - ##### m_max

            double m_max

      - ##### m_min

            double m_min

      - ##### m_outputInfoRetrievalStats

            boolean m_outputInfoRetrievalStats

      - ##### m_reset

            boolean m_reset

      - ##### m_statusFrequency

            int m_statusFrequency

      - ##### m_textListeners

            Vector<TextListener> m_textListeners

      - ##### m_window

            LinkedList<Instance> m_window

      - ##### m_windowedPreds

            LinkedList<double[]> m_windowedPreds

      - ##### m_windowEval

            Evaluation m_windowEval

      - ##### m_windowSize

            int m_windowSize

  - ### Class weka.gui.beans.IncrementalClassifierEvaluatorCustomizer

    class IncrementalClassifierEvaluatorCustomizer extends JPanel implements Serializable
    serialVersionUID:
      443506897387629418L

    - #### Serialized Fields

      - ##### m_evaluator

            IncrementalClassifierEvaluator m_evaluator

      - ##### m_freqBackup

            int m_freqBackup

      - ##### m_ieEditor

            PropertySheetPanel m_ieEditor

      - ##### m_modifyListener

            BeanCustomizer.ModifyListener m_modifyListener

      - ##### m_parent

            Window m_parent

      - ##### m_pcSupport

            PropertyChangeSupport m_pcSupport

        for serialization

      - ##### m_perClassBackup

            boolean m_perClassBackup

  - ### Class weka.gui.beans.IncrementalClassifierEvent

    class IncrementalClassifierEvent extends EventObject implements Serializable
    serialVersionUID:
      28979464317643232L

    - #### Serialized Fields

      - ##### m_classifier

            Classifier m_classifier

      - ##### m_currentInstance

            Instance m_currentInstance

      - ##### m_status

            int m_status

      - ##### m_structure

            Instances m_structure

  - ### Class weka.gui.beans.InstanceEvent

    class InstanceEvent extends EventObject implements Serializable
    serialVersionUID:
      6104920894559423946L

    - #### Serialized Fields

      - ##### m_formatNotificationOnly

            boolean m_formatNotificationOnly

        for FORMAT_AVAILABLE, if this is true then it indicates that this is not the actual start of stream processing, but rather that a file/source has changed via the user from the UI

      - ##### m_instance

            Instance m_instance

      - ##### m_status

            int m_status

      - ##### m_structure

            Instances m_structure

  - ### Class weka.gui.beans.InstanceStreamToBatchMaker

    class InstanceStreamToBatchMaker extends JPanel implements Serializable
    serialVersionUID:
      -7037141087208627799L

    - #### Serialized Fields

      - ##### m_batch

            List<Instance> m_batch

        Collects up the instances.

      - ##### m_dataListeners

            ArrayList<DataSourceListener> m_dataListeners

      - ##### m_listenee

            Object m_listenee

        Component connected to us.

      - ##### m_structure

            Instances m_structure

      - ##### m_visual

            BeanVisual m_visual

  - ### Class weka.gui.beans.InteractiveTableModel

    class InteractiveTableModel extends InteractiveTableModel implements Serializable
    serialVersionUID:
      7628124449228704885L

  - ### Class weka.gui.beans.InteractiveTablePanel

    class InteractiveTablePanel extends InteractiveTablePanel implements Serializable
    serialVersionUID:
      -5331129312037269302L

  - ### Class weka.gui.beans.Join

    class Join extends JPanel implements Serializable
    serialVersionUID:
      398021880509558185L

    - #### Serialized Fields

      - ##### m_busy

            boolean m_busy

        True if we are busy

      - ##### m_dataListeners

            ArrayList<DataSourceListener> m_dataListeners

        Downstream steps listening to batch data events

      - ##### m_firstInput

            Object m_firstInput

        The first source of data

      - ##### m_firstInputConnectionType

            String m_firstInputConnectionType

        Connection type of the first input

      - ##### m_firstIsWaiting

            boolean m_firstIsWaiting

        True if the first input stream is waiting due to a full buffer (incremental mode only)

      - ##### m_ie

            InstanceEvent m_ie

        Instance event to use for incremental mode

      - ##### m_incomingBatchConnections

            boolean m_incomingBatchConnections

        Upstream components sending us data

      - ##### m_instanceListeners

            ArrayList<InstanceListener> m_instanceListeners

        Downstream steps listening to instance events

      - ##### m_keyIndexesOne

            int[] m_keyIndexesOne

        Indexes of the key fields for the first input

      - ##### m_keyIndexesTwo

            int[] m_keyIndexesTwo

        Indexes of the key fields for the second input

      - ##### m_keySpec

            String m_keySpec

        Holds the internal representation of the key specification

      - ##### m_runningIncrementally

            boolean m_runningIncrementally

        True if the step is running incrementally

      - ##### m_secondInput

            Object m_secondInput

        The second source of data

      - ##### m_secondInputConnectionType

            String m_secondInputConnectionType

        Connection type of the second input

      - ##### m_secondIsWaiting

            boolean m_secondIsWaiting

        True if the second input stream is waiting due to a full buffer (incremental mode only)

      - ##### m_stopRequested

            AtomicBoolean m_stopRequested

        True if the step has been told to stop processing

      - ##### m_stringAttIndexesOne

            Map<String,Integer> m_stringAttIndexesOne

        Holds indexes of string attributes, keyed by attribute name

      - ##### m_stringAttIndexesTwo

            Map<String,Integer> m_stringAttIndexesTwo

        Holds indexes of string attributes, keyed by attribute name

      - ##### m_stringAttsPresent

            boolean m_stringAttsPresent

        True if string attributes are present in the incoming data

      - ##### m_visual

            BeanVisual m_visual

        Default visual for data sources

  - ### Class weka.gui.beans.Join.InstanceHolder

    class InstanceHolder extends Object implements Serializable
    serialVersionUID:
      -2554438923824758088L

    - #### Serialized Fields

      - ##### m_instance

            Instance m_instance

        The instance

      - ##### m_stringVals

            Map<String,String> m_stringVals

        for incremental operation, if string attributes are present then we need to store them with each instance - since incremental streaming in the knowledge flow only maintains one string value in memory (and hence in the header) at any one time

  - ### Class weka.gui.beans.JoinCustomizer

    class JoinCustomizer extends JPanel implements Serializable
    serialVersionUID:
      5797383368777382010L

    - #### Serialized Fields

      - ##### m_addOneBut

            JButton m_addOneBut

      - ##### m_addTwoBut

            JButton m_addTwoBut

      - ##### m_deleteOneBut

            JButton m_deleteOneBut

      - ##### m_deleteTwoBut

            JButton m_deleteTwoBut

      - ##### m_downOneBut

            JButton m_downOneBut

      - ##### m_downTwoBut

            JButton m_downTwoBut

      - ##### m_env

            Environment m_env

      - ##### m_firstKeyFields

            JComboBox m_firstKeyFields

      - ##### m_firstList

            JList m_firstList

      - ##### m_firstListModel

            DefaultListModel m_firstListModel

      - ##### m_join

            Join m_join

      - ##### m_modifyL

            BeanCustomizer.ModifyListener m_modifyL

      - ##### m_parent

            Window m_parent

      - ##### m_secondKeyFields

            JComboBox m_secondKeyFields

      - ##### m_secondList

            JList m_secondList

      - ##### m_secondListModel

            DefaultListModel m_secondListModel

      - ##### m_tempEditor

            PropertySheetPanel m_tempEditor

      - ##### m_upOneBut

            JButton m_upOneBut

      - ##### m_upTwoBut

            JButton m_upTwoBut

  - ### Class weka.gui.beans.KnowledgeFlowApp

    class KnowledgeFlowApp extends JPanel implements Serializable
    serialVersionUID:
      -7064906770289728431L

    - #### Serialized Fields

      - ##### m_allowMultipleTabs

            boolean m_allowMultipleTabs

        Whether to allow more than one tab or not

      - ##### m_bcSupport

            BeanContextSupport m_bcSupport

      - ##### m_beanLayout

            weka.gui.beans.KnowledgeFlowApp.BeanLayout m_beanLayout

        The layout area

      - ##### m_componentTree

            JTree m_componentTree

        Palette of components stored in a JTree

      - ##### m_configAndPerspectives

            JPanel m_configAndPerspectives

        Panel to hold the perspectives toolbar and config button

      - ##### m_configAndPerspectivesVisible

            boolean m_configAndPerspectivesVisible

        Whether the perspectives toolbar is visible at present (will never be visible if there are no plugin perspectives installed)

      - ##### m_copyB

            JButton m_copyB

      - ##### m_cutB

            JButton m_cutB

      - ##### m_deleteB

            JButton m_deleteB

      - ##### m_editElement

            BeanInstance m_editElement

        Reference to bean being manipulated

      - ##### m_FileChooser

            WekaFileChooser m_FileChooser

        The file chooser for selecting layout files

      - ##### m_firstUserComponentOpp

            boolean m_firstUserComponentOpp

      - ##### m_flowEnvironment

            Environment m_flowEnvironment

        Environment variables for the current flow

      - ##### m_FlowHeight

            int m_FlowHeight

        the flow layout height

      - ##### m_FlowWidth

            int m_FlowWidth

        the flow layout width

      - ##### m_fontM

            FontMetrics m_fontM

      - ##### m_gridSpacing

            int m_gridSpacing

        Snap-to-grid spacing

      - ##### m_groupB

            JButton m_groupB

      - ##### m_helpB

            JButton m_helpB

      - ##### m_KfFilter

            FileFilter m_KfFilter

        A filter to ensure only KnowledgeFlow files in binary format get shown in the chooser

      - ##### m_KOMLFilter

            FileFilter m_KOMLFilter

        A filter to ensure only KnowledgeFlow files in KOML format get shown in the chooser

      - ##### m_layoutZoom

            int m_layoutZoom

      - ##### m_loadB

            JButton m_loadB

      - ##### m_logPanel

            weka.gui.beans.KnowledgeFlowApp.KFLogPanel m_logPanel

      - ##### m_mainKFPerspective

            KnowledgeFlowApp.MainKFPerspective m_mainKFPerspective

        Shortcut to the main perspective

      - ##### m_mode

            int m_mode

      - ##### m_newB

            JButton m_newB

      - ##### m_noteB

            JButton m_noteB

      - ##### m_oldX

            int m_oldX

        Used to record screen coordinates during move, select and connect operations

      - ##### m_oldY

            int m_oldY

        Used to record screen coordinates during move, select and connect operations

      - ##### m_pasteB

            JButton m_pasteB

      - ##### m_pasteBuffer

            StringBuffer m_pasteBuffer

        The clip board

      - ##### m_perspectiveCache

            Map<String,KnowledgeFlowApp.KFPerspective> m_perspectiveCache

        Those perspectives that have been instantiated

      - ##### m_perspectiveConfigurer

            AttributeSelectionPanel m_perspectiveConfigurer

      - ##### m_perspectiveDataLoadThread

            Thread m_perspectiveDataLoadThread

        Thread for loading data for perspectives

      - ##### m_perspectiveGroup

            ButtonGroup m_perspectiveGroup

        Button group to manage all perspective toggle buttons

      - ##### m_perspectiveHolder

            JPanel m_perspectiveHolder

        Component that holds the currently visible perspective

      - ##### m_perspectives

            List<KnowledgeFlowApp.KFPerspective> m_perspectives

        Holds the list of currently loaded perspectives. Element at 0 is always the main KF data mining flow perspective

      - ##### m_perspectiveToolBar

            JToolBar m_perspectiveToolBar

        Toolbar to hold the perspective buttons

      - ##### m_playB

            JButton m_playB

      - ##### m_playBB

            JButton m_playBB

      - ##### m_pluginPerspectiveLookup

            Map<String,String> m_pluginPerspectiveLookup

        Map of all plugin perspectives

      - ##### m_pointerB

            JButton m_pointerB

      - ##### m_PreferredExtension

            String m_PreferredExtension

        the preferred file extension

      - ##### m_saveB

            JButton m_saveB

      - ##### m_saveBB

            JButton m_saveBB

      - ##### m_ScrollBarIncrementComponents

            int m_ScrollBarIncrementComponents

        the scrollbar increment of the components scrollpane

      - ##### m_ScrollBarIncrementLayout

            int m_ScrollBarIncrementLayout

        the scrollbar increment of the layout scrollpane

      - ##### m_selectAllB

            JButton m_selectAllB

      - ##### m_showFileMenu

            boolean m_showFileMenu

      - ##### m_snapToGridB

            JToggleButton m_snapToGridB

      - ##### m_sourceEventSetDescriptor

            EventSetDescriptor m_sourceEventSetDescriptor

        Event set descriptor for the bean being manipulated

      - ##### m_startX

            int m_startX

      - ##### m_startY

            int m_startY

      - ##### m_stopB

            JButton m_stopB

      - ##### m_templatesB

            JButton m_templatesB

      - ##### m_togglePerspectivesB

            JButton m_togglePerspectivesB

      - ##### m_toolBarBean

            Object m_toolBarBean

        Holds the selected toolbar bean

      - ##### m_undoB

            JButton m_undoB

      - ##### m_untitledCount

            int m_untitledCount

        Number of untitled tabs so far

      - ##### m_userCompNode

            DefaultMutableTreeNode m_userCompNode

        The node of the JTree that holds "user" (metabean) components

      - ##### m_userComponents

            Vector<Object> m_userComponents

      - ##### m_UserComponentsInXML

            boolean m_UserComponentsInXML

        whether to store the user components in XML or in binary format

      - ##### m_XMLFilter

            FileFilter m_XMLFilter

        A filter to ensure only KnowledgeFlow layout files in XML format get shown in the chooser

      - ##### m_XStreamFilter

            FileFilter m_XStreamFilter

        A filter to ensure only KnowledgeFlow files in XStream format get shown in the chooser

      - ##### m_zoomInB

            JButton m_zoomInB

      - ##### m_zoomOutB

            JButton m_zoomOutB

  - ### Class weka.gui.beans.KnowledgeFlowApp.BeanIconRenderer

    class BeanIconRenderer extends DefaultTreeCellRenderer implements Serializable
    serialVersionUID:
      -4488876734500244945L

  - ### Class weka.gui.beans.KnowledgeFlowApp.BeanLayout

    class BeanLayout extends PrintablePanel implements Serializable
    serialVersionUID:
      -146377012429662757L

  - ### Class weka.gui.beans.KnowledgeFlowApp.InvisibleNode

    class InvisibleNode extends DefaultMutableTreeNode implements Serializable
    serialVersionUID:
      -9064396835384819887L

    - #### Serialized Fields

      - ##### m_isVisible

            boolean m_isVisible

  - ### Class weka.gui.beans.KnowledgeFlowApp.InvisibleTreeModel

    class InvisibleTreeModel extends DefaultTreeModel implements Serializable
    serialVersionUID:
      6940101211275068260L

    - #### Serialized Fields

      - ##### m_filterIsActive

            boolean m_filterIsActive

  - ### Class weka.gui.beans.KnowledgeFlowApp.JTreeLeafDetails

    class JTreeLeafDetails extends Object implements Serializable
    serialVersionUID:
      6197221540272931626L

    - #### Serialized Fields

      - ##### m_fullyQualifiedCompName

            String m_fullyQualifiedCompName

        fully qualified bean name

      - ##### m_isMeta

            boolean m_isMeta

        true if this is a MetaBean (user component)

      - ##### m_leafLabel

            String m_leafLabel

        the label (usually derived from the qualified name or wrapped algorithm) for the leaf

      - ##### m_metaBean

            Vector<Object> m_metaBean

        XML serialized MetaBean (if this is a user component)

      - ##### m_toolTipText

            String m_toolTipText

        tool tip text to display

      - ##### m_wekaAlgoName

            String m_wekaAlgoName

        the fully qualified wrapped weka algorithm name

  - ### Class weka.gui.beans.KnowledgeFlowApp.KFLogPanel

    class KFLogPanel extends LogPanel implements Serializable
    serialVersionUID:
      -2224509243343105276L

  - ### Class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

    class MainKFPerspective extends JPanel implements Serializable
    serialVersionUID:
      7666381888012259527L

    - #### Serialized Fields

      - ##### m_beanLayouts

            List<weka.gui.beans.KnowledgeFlowApp.BeanLayout> m_beanLayouts

        List of layouts - one for each tab

      - ##### m_editedList

            List<Boolean> m_editedList

        Keeps track of which tabs have been edited but not saved

      - ##### m_environmentSettings

            List<Environment> m_environmentSettings

        List of environment variable settings - one for each tab

      - ##### m_executingList

            List<Boolean> m_executingList

        Keeps track of which tabs have flows that are executing

      - ##### m_executionThreads

            List<weka.gui.beans.KnowledgeFlowApp.RunThread> m_executionThreads

        Keeps track of the threads used for execution

      - ##### m_filePaths

            List<File> m_filePaths

        List of flow file paths - one for each tab

      - ##### m_flowTabs

            JTabbedPane m_flowTabs

        Holds the tabs of the perspective

      - ##### m_logPanels

            List<weka.gui.beans.KnowledgeFlowApp.KFLogPanel> m_logPanels

        List of log panels - one for each tab

      - ##### m_nodeTextIndex

            Map<String,DefaultMutableTreeNode> m_nodeTextIndex

      - ##### m_selectedBeans

            List<Vector<Object>> m_selectedBeans

        Keeps track of any highlighted beans on the canvas for a tab

      - ##### m_undoBufferList

            List<Stack<File>> m_undoBufferList

        Keeps track of the undo buffers for each tab

      - ##### m_zoomSettings

            List<Integer> m_zoomSettings

        List of zoom settings - one for each tab

  - ### Class weka.gui.beans.Loader

    class Loader extends AbstractDataSource implements Serializable
    serialVersionUID:
      1993738191961163027L

    - #### Serialization Methods

      - ##### readObject

        private void readObject(ObjectInputStream aStream) throws IOException, ClassNotFoundException
        Throws:
          `IOException`
          `ClassNotFoundException`

      - ##### readResolve

        private Object readResolve() throws ObjectStreamException
        Throws:
          `ObjectStreamException`

    - #### Serialized Fields

      - ##### m_dataSetEventTargets

            int m_dataSetEventTargets

      - ##### m_dbSet

            boolean m_dbSet

        Flag indicating that a database has already been configured

      - ##### m_globalInfo

            String m_globalInfo

        Global info for the wrapped loader (if it exists).

      - ##### m_ie

            InstanceEvent m_ie

      - ##### m_instanceEventTargets

            int m_instanceEventTargets

        Keep track of how many listeners for different types of events there are.

      - ##### m_ioThread

            weka.gui.beans.Loader.LoadThread m_ioThread

        Thread for doing IO in

      - ##### m_Loader

            Loader m_Loader

        Loader

      - ##### m_state

            int m_state

      - ##### m_stopped

            boolean m_stopped

        Asked to stop?

  - ### Class weka.gui.beans.LoaderCustomizer

    class LoaderCustomizer extends JPanel implements Serializable
    serialVersionUID:
      6990446313118930298L

    - #### Serialized Fields

      - ##### m_backup

            Loader m_backup

      - ##### m_dbaseURLText

            EnvironmentField m_dbaseURLText

      - ##### m_dbProps

            FileEnvironmentField m_dbProps

      - ##### m_dsLoader

            Loader m_dsLoader

      - ##### m_env

            Environment m_env

      - ##### m_fileChooser

            WekaFileChooser m_fileChooser

      - ##### m_fileChooserFrame

            JDialog m_fileChooserFrame

      - ##### m_fileText

            EnvironmentField m_fileText

      - ##### m_keyText

            EnvironmentField m_keyText

      - ##### m_LoaderEditor

            PropertySheetPanel m_LoaderEditor

      - ##### m_modifyListener

            BeanCustomizer.ModifyListener m_modifyListener

      - ##### m_parentWindow

            Window m_parentWindow

      - ##### m_passwordText

            JPasswordField m_passwordText

      - ##### m_pcSupport

            PropertyChangeSupport m_pcSupport

      - ##### m_queryText

            EnvironmentField m_queryText

      - ##### m_userNameText

            EnvironmentField m_userNameText

  - ### Class weka.gui.beans.LogPanel

    class LogPanel extends JPanel implements Serializable
    serialVersionUID:
      6583097154513435548L

    - #### Serialized Fields

      - ##### m_formatter

            DecimalFormat m_formatter

        For formatting timer digits

      - ##### m_logPanel

            LogPanel m_logPanel

        The log panel to delegate log messages to.

      - ##### m_table

            JTable m_table

        The table for the status area

      - ##### m_tableIndexes

            HashMap<String,Integer> m_tableIndexes

        Holds the index (line number) in the JTable of each component being tracked.

      - ##### m_tableModel

            DefaultTableModel m_tableModel

        The table model for the JTable used in the status area

      - ##### m_tabs

            JTabbedPane m_tabs

        Tabbed pane to hold both the status and the log

      - ##### m_timers

            HashMap<String,Timer> m_timers

        Holds the timers associated with each component being tracked.

  - ### Class weka.gui.beans.MetaBean

    class MetaBean extends JPanel implements Serializable
    serialVersionUID:
      -6582768902038027077L

    - #### Serialized Fields

      - ##### m_associatedConnections

            Vector<BeanConnection> m_associatedConnections

      - ##### m_inputs

            Vector<Object> m_inputs

      - ##### m_originalCoords

            Vector<Point> m_originalCoords

      - ##### m_outputs

            Vector<Object> m_outputs

      - ##### m_subFlow

            Vector<Object> m_subFlow

      - ##### m_subFlowPreview

            ImageIcon m_subFlowPreview

      - ##### m_visual

            BeanVisual m_visual

      - ##### m_xCreate

            int m_xCreate

      - ##### m_xDrop

            int m_xDrop

      - ##### m_yCreate

            int m_yCreate

      - ##### m_yDrop

            int m_yDrop

  - ### Class weka.gui.beans.ModelPerformanceChart

    class ModelPerformanceChart extends JPanel implements Serializable
    serialVersionUID:
      -4602034200071195924L

    - #### Serialized Fields

      - ##### m_additionalOptions

            String m_additionalOptions

        Additional options for the offscreen renderer

      - ##### m_bcSupport

            BeanContextChildSupport m_bcSupport

        BeanContextChild support

      - ##### m_design

            boolean m_design

        True if this bean's appearance is the design mode appearance

      - ##### m_framePoppedUp

            boolean m_framePoppedUp

      - ##### m_headlessEvents

            List<EventObject> m_headlessEvents

        Events received and stored during headless execution

      - ##### m_height

            String m_height

        Height of offscreen plots

      - ##### m_imageListeners

            ArrayList<ImageListener> m_imageListeners

      - ##### m_listenees

            List<Object> m_listenees

      - ##### m_offscreenRendererName

            String m_offscreenRendererName

        Name of the renderer to use for offscreen chart rendering

      - ##### m_visual

            BeanVisual m_visual

      - ##### m_width

            String m_width

        Width of offscreen plots

      - ##### m_xAxis

            String m_xAxis

        The name of the attribute to use for the x-axis of offscreen plots. If left empty, False Positive Rate is used for threshold curves

      - ##### m_yAxis

            String m_yAxis

        The name of the attribute to use for the y-axis of offscreen plots. If left empty, True Positive Rate is used for threshold curves

  - ### Class weka.gui.beans.ModelPerformanceChartCustomizer

    class ModelPerformanceChartCustomizer extends JPanel implements Serializable
    serialVersionUID:
      27802741348090392L

    - #### Serialized Fields

      - ##### m_env

            Environment m_env

      - ##### m_height

            EnvironmentField m_height

      - ##### m_heightBack

            String m_heightBack

      - ##### m_modelPC

            ModelPerformanceChart m_modelPC

      - ##### m_modifyListener

            BeanCustomizer.ModifyListener m_modifyListener

      - ##### m_opts

            EnvironmentField m_opts

      - ##### m_optsBack

            String m_optsBack

      - ##### m_parent

            Window m_parent

      - ##### m_rendererCombo

            JComboBox m_rendererCombo

      - ##### m_rendererNameBack

            String m_rendererNameBack

      - ##### m_width

            EnvironmentField m_width

      - ##### m_widthBack

            String m_widthBack

      - ##### m_xAxis

            EnvironmentField m_xAxis

      - ##### m_xAxisBack

            String m_xAxisBack

      - ##### m_yAxis

            EnvironmentField m_yAxis

      - ##### m_yAxisBack

            String m_yAxisBack

  - ### Class weka.gui.beans.Note

    class Note extends JPanel implements Serializable
    serialVersionUID:
      -7272355421198069040L

    - #### Serialized Fields

      - ##### m_fontSizeAdjust

            int m_fontSizeAdjust

        Adjustment for the font size

      - ##### m_label

            JLabel m_label

        The label that displays the note text

      - ##### m_noteText

            String m_noteText

        The note text

  - ### Class weka.gui.beans.NoteCustomizer

    class NoteCustomizer extends JPanel implements Serializable
    serialVersionUID:
      995648616684953391L

    - #### Serialized Fields

      - ##### m_modifyListener

            BeanCustomizer.ModifyListener m_modifyListener

        Listener that wants to know the the modified status of the object that we're customizing

      - ##### m_note

            Note m_note

        the note to be edited

      - ##### m_parentWindow

            Window m_parentWindow

        the parent window

      - ##### m_textArea

            JTextArea m_textArea

        text area for displaying the note's text

  - ### Class weka.gui.beans.PredictionAppender

    class PredictionAppender extends JPanel implements Serializable
    serialVersionUID:
      -2987740065058976673L

    - #### Serialized Fields

      - ##### m_appendProbabilities

            boolean m_appendProbabilities

        Append classifier's predicted probabilities (if the class is discrete and the classifier is a distribution classifier)

      - ##### m_dataSourceListeners

            Vector<DataSourceListener> m_dataSourceListeners

        Objects listenening for dataset events

      - ##### m_format

            Instances m_format

        Format of instances to be produced.

      - ##### m_instanceEvent

            InstanceEvent m_instanceEvent

      - ##### m_instanceListeners

            Vector<InstanceListener> m_instanceListeners

        Objects listening for instances events

      - ##### m_listenee

            Object m_listenee

        Non null if this object is a target for any events.

      - ##### m_testSetListeners

            Vector<TestSetListener> m_testSetListeners

        Objects listening for test set events

      - ##### m_trainingSetListeners

            Vector<TrainingSetListener> m_trainingSetListeners

        Objects listening for training set events

      - ##### m_visual

            BeanVisual m_visual

  - ### Class weka.gui.beans.PredictionAppenderCustomizer

    class PredictionAppenderCustomizer extends JPanel implements Serializable
    serialVersionUID:
      6884933202506331888L

    - #### Serialized Fields

      - ##### m_appender

            PredictionAppender m_appender

      - ##### m_appendProbsBackup

            boolean m_appendProbsBackup

      - ##### m_modifyListener

            BeanCustomizer.ModifyListener m_modifyListener

      - ##### m_paEditor

            PropertySheetPanel m_paEditor

      - ##### m_parent

            Window m_parent

      - ##### m_pcSupport

            PropertyChangeSupport m_pcSupport

  - ### Class weka.gui.beans.Saver

    class Saver extends AbstractDataSink implements Serializable
    serialVersionUID:
      5371716690308950755L

    - #### Serialization Methods

      - ##### readObject

        private void readObject(ObjectInputStream aStream) throws IOException, ClassNotFoundException
        Throws:
          `IOException`
          `ClassNotFoundException`

    - #### Serialized Fields

      - ##### m_count

            int m_count

        Count for structure available messages

      - ##### m_dataSet

            Instances m_dataSet

        Holds the instances to be saved

      - ##### m_fileName

            String m_fileName

        The relation name that becomes part of the file name

      - ##### m_globalInfo

            String m_globalInfo

        Global info for the wrapped loader (if it exists).

      - ##### m_isDBSaver

            boolean m_isDBSaver

        Flag indicating that instances will be saved to database. Used because structure information can only be sent after a database has been configured.

      - ##### m_relationNameForFilename

            boolean m_relationNameForFilename

        For file-based savers - if true (default), relation name is used as the primary part of the filename. If false, then the prefix is used as the filename. Useful for preventing filenames from getting too long when there are many filters in a flow.

      - ##### m_Saver

            Saver m_Saver

        Saver

      - ##### m_SaverTemplate

            Saver m_SaverTemplate

      - ##### m_structure

            Instances m_structure

        Holds the structure

  - ### Class weka.gui.beans.SaverCustomizer

    class SaverCustomizer extends JPanel implements Serializable
    serialVersionUID:
      -4874208115942078471L

    - #### Serialized Fields

      - ##### m_dbaseURLText

            EnvironmentField m_dbaseURLText

      - ##### m_dbProps

            FileEnvironmentField m_dbProps

      - ##### m_directoryText

            EnvironmentField m_directoryText

      - ##### m_dsSaver

            Saver m_dsSaver

      - ##### m_env

            Environment m_env

      - ##### m_fileChooser

            WekaFileChooser m_fileChooser

      - ##### m_fileChooserFrame

            JDialog m_fileChooserFrame

      - ##### m_idBox

            JCheckBox m_idBox

      - ##### m_modifyListener

            BeanCustomizer.ModifyListener m_modifyListener

      - ##### m_parentWindow

            Window m_parentWindow

      - ##### m_passwordText

            JPasswordField m_passwordText

      - ##### m_pcSupport

            PropertyChangeSupport m_pcSupport

      - ##### m_prefixText

            EnvironmentField m_prefixText

      - ##### m_relationNameForFilename

            JCheckBox m_relationNameForFilename

      - ##### m_relativeFilePath

            JCheckBox m_relativeFilePath

      - ##### m_SaverEditor

            PropertySheetPanel m_SaverEditor

      - ##### m_tabBox

            JCheckBox m_tabBox

      - ##### m_tableText

            EnvironmentField m_tableText

      - ##### m_truncateBox

            JCheckBox m_truncateBox

      - ##### m_userNameText

            EnvironmentField m_userNameText

  - ### Class weka.gui.beans.ScatterPlotMatrix

    class ScatterPlotMatrix extends DataVisualizer implements Serializable
    serialVersionUID:
      -657856527563507491L

    - #### Serialized Fields

      - ##### m_matrixPanel

            MatrixPanel m_matrixPanel

  - ### Class weka.gui.beans.SerializedModelSaver

    class SerializedModelSaver extends JPanel implements Serializable
    serialVersionUID:
      3956528599473814287L

    - #### Serialization Methods

      - ##### readObject

        private void readObject(ObjectInputStream aStream) throws IOException, ClassNotFoundException
        Throws:
          `IOException`
          `ClassNotFoundException`

    - #### Serialized Fields

      - ##### m_directory

            File m_directory

        The directory to hold the saved model(s)

      - ##### m_fileFormat

            Tag m_fileFormat

        File format stuff

      - ##### m_filenamePrefix

            String m_filenamePrefix

        The prefix for the file name (model + training set info will be appended)

      - ##### m_includeRelationName

            boolean m_includeRelationName

        include relation name in filename

      - ##### m_incrementalSaveSchedule

            int m_incrementalSaveSchedule

        How often to save an incremental classifier (<= 0 means only at the end of the stream)

      - ##### m_listenee

            Object m_listenee

        Non null if this object is a target for any events. Provides for the simplest case when only one incomming connection is allowed.

      - ##### m_useRelativePath

            boolean m_useRelativePath

        relative path for the directory (relative to the user.dir (startup directory))?

      - ##### m_visual

            BeanVisual m_visual

        Default visual for data sources

  - ### Class weka.gui.beans.SerializedModelSaverCustomizer

    class SerializedModelSaverCustomizer extends JPanel implements Serializable
    serialVersionUID:
      -4874208115942078471L

    - #### Serialized Fields

      - ##### m_directoryBackup

            File m_directoryBackup

      - ##### m_directoryText

            EnvironmentField m_directoryText

      - ##### m_env

            Environment m_env

      - ##### m_fileChooser

            WekaFileChooser m_fileChooser

      - ##### m_fileChooserFrame

            JDialog m_fileChooserFrame

      - ##### m_fileFormatBox

            JComboBox m_fileFormatBox

      - ##### m_formatBackup

            Tag m_formatBackup

      - ##### m_includeRelationName

            JCheckBox m_includeRelationName

      - ##### m_incrementalSaveSchedule

            JTextField m_incrementalSaveSchedule

      - ##### m_modifyListener

            BeanCustomizer.ModifyListener m_modifyListener

      - ##### m_parentWindow

            Window m_parentWindow

      - ##### m_pcSupport

            PropertyChangeSupport m_pcSupport

      - ##### m_prefixBackup

            String m_prefixBackup

      - ##### m_prefixText

            EnvironmentField m_prefixText

      - ##### m_relationBackup

            boolean m_relationBackup

      - ##### m_relativeBackup

            boolean m_relativeBackup

      - ##### m_relativeFilePath

            JCheckBox m_relativeFilePath

      - ##### m_SaverEditor

            PropertySheetPanel m_SaverEditor

      - ##### m_smSaver

            SerializedModelSaver m_smSaver

  - ### Class weka.gui.beans.ShadowBorder

    class ShadowBorder extends AbstractBorder implements Serializable
    serialVersionUID:
      -2117842133475125463L

    - #### Serialized Fields

      - ##### m_color

            Color m_color

        the color of the drop shadow

      - ##### m_width

            int m_width

        The width in pixels of the drop shadow

  - ### Class weka.gui.beans.Sorter

    class Sorter extends JPanel implements Serializable
    serialVersionUID:
      4978227384322482115L

    - #### Serialized Fields

      - ##### m_bufferSize

            String m_bufferSize

        Size of the in-memory buffer

      - ##### m_bufferSizeI

            int m_bufferSizeI

        Size of the in-memory buffer after resolving any environment vars

      - ##### m_busy

            boolean m_busy

        True if we are busy

      - ##### m_connectedFormat

            Instances m_connectedFormat

        format of instances for current incoming connection (if any)

      - ##### m_connectionType

            String m_connectionType

        The type of the incoming connection

      - ##### m_dataListeners

            ArrayList<DataSourceListener> m_dataListeners

        Downstream steps listening to batch data events

      - ##### m_ie

            InstanceEvent m_ie

        For printing status updates in incremental mode

      - ##### m_instanceListeners

            ArrayList<InstanceListener> m_instanceListeners

        Downstream steps listening to instance events

      - ##### m_listenee

            Object m_listenee

        Step talking to us

      - ##### m_sortDetails

            String m_sortDetails

        Holds the internal textual description of the sort definitions

      - ##### m_stopRequested

            AtomicBoolean m_stopRequested

        True if a stop has been requested

      - ##### m_stringAttIndexes

            Map<String,Integer> m_stringAttIndexes

        Holds indexes of string attributes, keyed by attribute name

      - ##### m_tempDirectory

            String m_tempDirectory

        The directory to hold the temp files - if not set the system tmp directory is used

      - ##### m_visual

            BeanVisual m_visual

        Default visual for data sources

  - ### Class weka.gui.beans.Sorter.InstanceHolder

    class InstanceHolder extends Object implements Serializable
    serialVersionUID:
      -3985730394250172995L

    - #### Serialized Fields

      - ##### m_fileNumber

            int m_fileNumber

        index into the list of files on disk

      - ##### m_instance

            Instance m_instance

        The instance

      - ##### m_stringVals

            Map<String,String> m_stringVals

        for incremental operation, if string attributes are present then we need to store them with each instance - since incremental streaming in the knowledge flow only maintains one string value in memory (and hence in the header) at any one time

  - ### Class weka.gui.beans.SorterCustomizer

    class SorterCustomizer extends JPanel implements Serializable
    serialVersionUID:
      -4860246697276275408L

    - #### Serialized Fields

      - ##### m_attCombo

            JComboBox m_attCombo

      - ##### m_buffSize

            EnvironmentField m_buffSize

      - ##### m_deleteBut

            JButton m_deleteBut

      - ##### m_descending

            JComboBox m_descending

      - ##### m_downBut

            JButton m_downBut

      - ##### m_env

            Environment m_env

      - ##### m_list

            JList m_list

      - ##### m_listModel

            DefaultListModel m_listModel

      - ##### m_modifyL

            BeanCustomizer.ModifyListener m_modifyL

      - ##### m_newBut

            JButton m_newBut

      - ##### m_parent

            Window m_parent

      - ##### m_sorter

            Sorter m_sorter

        The Sorter we are editing

      - ##### m_tempDir

            FileEnvironmentField m_tempDir

      - ##### m_tempEditor

            PropertySheetPanel m_tempEditor

      - ##### m_upBut

            JButton m_upBut

  - ### Class weka.gui.beans.SQLViewerPerspective

    class SQLViewerPerspective extends JPanel implements Serializable
    serialVersionUID:
      3684166225482042972L

    - #### Serialized Fields

      - ##### m_mainPerspective

            KnowledgeFlowApp.MainKFPerspective m_mainPerspective

      - ##### m_newFlowBut

            JButton m_newFlowBut

      - ##### m_viewer

            SqlViewer m_viewer

  - ### Class weka.gui.beans.StreamThroughput

    class StreamThroughput extends Object implements Serializable
    serialVersionUID:
      2820675210555581676L

  - ### Class weka.gui.beans.StripChart

    class StripChart extends JPanel implements Serializable
    serialVersionUID:
      1483649041577695019L

    - #### Serialization Methods

      - ##### readObject

        private void readObject(ObjectInputStream ois) throws IOException, ClassNotFoundException
        Provide some necessary initialization after object has been deserialized.
        Parameters:
          `ois` - an `ObjectInputStream` value
        Throws:
          `IOException` - if an error occurs
          `ClassNotFoundException` - if an error occurs

    - #### Serialized Fields

      - ##### m_BackgroundColor

            Color m_BackgroundColor

        the background color.

      - ##### m_ce

            ChartEvent m_ce

      - ##### m_colorList

            Color[] m_colorList

        default colours for colouring lines

      - ##### m_dataList

            LinkedList<double[]> m_dataList

        Holds the data to be plotted. Entries in the list are arrays of y points.

      - ##### m_dataPoint

            double[] m_dataPoint

      - ##### m_iheight

            int m_iheight

        Width and height of the off screen image.

      - ##### m_iwidth

            int m_iwidth

      - ##### m_labelFont

            Font m_labelFont

      - ##### m_labelMetrics

            FontMetrics m_labelMetrics

      - ##### m_legendPanel

            weka.gui.beans.StripChart.LegendPanel m_legendPanel

        the legend.

      - ##### m_LegendPanelBorderColor

            Color m_LegendPanelBorderColor

        the color of the legend panel's border.

      - ##### m_legendText

            Vector<String> m_legendText

      - ##### m_listenee

            Object m_listenee

      - ##### m_max

            double m_max

        Max value for the y axis.

      - ##### m_min

            double m_min

        Min value for the y axis.

      - ##### m_oldMax

            double m_oldMax

      - ##### m_oldMin

            double m_oldMin

      - ##### m_previousY

            double[] m_previousY

      - ##### m_Printer

            PrintableComponent m_Printer

        the class responsible for printing

      - ##### m_refreshFrequency

            int m_refreshFrequency

        Plot every m_refreshFrequency'th point

      - ##### m_refreshWidth

            int m_refreshWidth

        Shift the plot by this many pixels every time a point is plotted

      - ##### m_scalePanel

            weka.gui.beans.StripChart.ScalePanel m_scalePanel

        the scale.

      - ##### m_userRefreshWidth

            int m_userRefreshWidth

      - ##### m_visual

            BeanVisual m_visual

      - ##### m_xCount

            int m_xCount

      - ##### m_xValFreq

            int m_xValFreq

        Print x axis labels every m_xValFreq points

      - ##### m_yScaleUpdate

            boolean m_yScaleUpdate

        Scale update requested.

  - ### Class weka.gui.beans.StripChartCustomizer

    class StripChartCustomizer extends JPanel implements Serializable
    serialVersionUID:
      7441741530975984608L

    - #### Serialized Fields

      - ##### m_cvEditor

            PropertySheetPanel m_cvEditor

      - ##### m_pcSupport

            PropertyChangeSupport m_pcSupport

  - ### Class weka.gui.beans.SubstringLabeler

    class SubstringLabeler extends JPanel implements Serializable
    serialVersionUID:
      6297059699297260134L

    - #### Serialized Fields

      - ##### m_addFilter

            Add m_addFilter

        Add filter for adding the new attribute

      - ##### m_attName

            String m_attName

        Name of the new attribute

      - ##### m_consumeNonMatchingInstances

            boolean m_consumeNonMatchingInstances

        For multi-valued labeled rules, whether or not to consume non-matching instances or output them with missing value for the match attribute.

      - ##### m_dataListeners

            ArrayList<DataSourceListener> m_dataListeners

        Downstream steps listening to data set events

      - ##### m_ie

            InstanceEvent m_ie

        Instance event to use

      - ##### m_instanceListeners

            ArrayList<InstanceListener> m_instanceListeners

        Downstream steps listening to instance events

      - ##### m_listenee

            Object m_listenee

        Component talking to us

      - ##### m_matchDetails

            String m_matchDetails

        Internally encoded list of match rules

      - ##### m_nominalBinary

            boolean m_nominalBinary

        Whether to make the binary match/non-match attribute a nominal (rather than numeric) binary attribute.

      - ##### m_visual

            BeanVisual m_visual

        Default visual filters

  - ### Class weka.gui.beans.SubstringLabelerCustomizer

    class SubstringLabelerCustomizer extends JPanel implements Serializable
    serialVersionUID:
      7636584212353183751L

    - #### Serialized Fields

      - ##### m_attListField

            EnvironmentField m_attListField

      - ##### m_consumeNonMatchingCheck

            JCheckBox m_consumeNonMatchingCheck

      - ##### m_deleteBut

            JButton m_deleteBut

      - ##### m_downBut

            JButton m_downBut

      - ##### m_env

            Environment m_env

      - ##### m_ignoreCaseCheck

            JCheckBox m_ignoreCaseCheck

      - ##### m_labeler

            SubstringLabeler m_labeler

      - ##### m_labelField

            EnvironmentField m_labelField

      - ##### m_list

            JList m_list

      - ##### m_listModel

            DefaultListModel m_listModel

      - ##### m_matchAttNameField

            EnvironmentField m_matchAttNameField

      - ##### m_matchField

            EnvironmentField m_matchField

      - ##### m_modifyL

            BeanCustomizer.ModifyListener m_modifyL

      - ##### m_newBut

            JButton m_newBut

      - ##### m_nominalBinaryCheck

            JCheckBox m_nominalBinaryCheck

      - ##### m_parent

            Window m_parent

      - ##### m_regexCheck

            JCheckBox m_regexCheck

      - ##### m_tempEditor

            PropertySheetPanel m_tempEditor

      - ##### m_upBut

            JButton m_upBut

  - ### Class weka.gui.beans.SubstringLabelerRules

    class SubstringLabelerRules extends Object implements Serializable
    serialVersionUID:
      1392983905562573599L

    - #### Serialized Fields

      - ##### m_attName

            String m_attName

        The name of the new "label" attribute

      - ##### m_consumeNonMatching

            boolean m_consumeNonMatching

        True if non matching instances should be "consumed" - i.e no output instance created

      - ##### m_hasLabels

            boolean m_hasLabels

        True if the rules have user supplied labels

      - ##### m_inputStructure

            Instances m_inputStructure

        The input structure

      - ##### m_matchRules

            List<SubstringLabelerRules.SubstringLabelerMatchRule> m_matchRules

        The list of rules

      - ##### m_nominalBinary

            boolean m_nominalBinary

        If not multiple labels then should new att be a nominal rather than numeric binary one?

      - ##### m_outputStructure

            Instances m_outputStructure

        The output structure

      - ##### m_statusMessagePrefix

            String m_statusMessagePrefix

        An optional prefix for status log messages

      - ##### m_voteLabels

            boolean m_voteLabels

  - ### Class weka.gui.beans.SubstringLabelerRules.SubstringLabelerMatchRule

    class SubstringLabelerMatchRule extends Object implements Serializable
    serialVersionUID:
      6518104085439241523L

    - #### Serialized Fields

      - ##### m_attsToApplyTo

            String m_attsToApplyTo

        The attributes to apply the match-replace rule to

      - ##### m_ignoreCase

            boolean m_ignoreCase

        True if case should be ignored when matching

      - ##### m_label

            String m_label

        The label (if any) for this rule

      - ##### m_labelS

            String m_labelS

        Resolved label string

      - ##### m_logger

            Logger m_logger

        Logger to use

      - ##### m_match

            String m_match

        The substring literal/regex to use for matching

      - ##### m_matchS

            String m_matchS

        Resolved match string

      - ##### m_regex

            boolean m_regex

        True if a regular expression match is to be used

      - ##### m_regexPattern

            Pattern m_regexPattern

        Precompiled regex pattern

      - ##### m_selectedAtts

            int[] m_selectedAtts

        Attributes to apply to

      - ##### m_statusMessagePrefix

            String m_statusMessagePrefix

        Status message prefix

  - ### Class weka.gui.beans.SubstringReplacer

    class SubstringReplacer extends JPanel implements Serializable
    serialVersionUID:
      5636877747903965818L

    - #### Serialized Fields

      - ##### m_ie

            InstanceEvent m_ie

        Instance event to use

      - ##### m_instanceListeners

            ArrayList<InstanceListener> m_instanceListeners

        Downstream steps listening to instance events

      - ##### m_listenee

            Object m_listenee

        Component sending us instances

      - ##### m_matchReplaceDetails

            String m_matchReplaceDetails

        Internally encoded list of match-replace rules

      - ##### m_visual

            BeanVisual m_visual

        Default visual filters

  - ### Class weka.gui.beans.SubstringReplacerCustomizer

    class SubstringReplacerCustomizer extends JPanel implements Serializable
    serialVersionUID:
      -1245155414691393809L

    - #### Serialized Fields

      - ##### m_attListField

            EnvironmentField m_attListField

      - ##### m_deleteBut

            JButton m_deleteBut

      - ##### m_downBut

            JButton m_downBut

      - ##### m_env

            Environment m_env

      - ##### m_ignoreCaseCheck

            JCheckBox m_ignoreCaseCheck

      - ##### m_list

            JList m_list

      - ##### m_listModel

            DefaultListModel m_listModel

      - ##### m_matchField

            EnvironmentField m_matchField

      - ##### m_modifyL

            BeanCustomizer.ModifyListener m_modifyL

      - ##### m_newBut

            JButton m_newBut

      - ##### m_parent

            Window m_parent

      - ##### m_regexCheck

            JCheckBox m_regexCheck

      - ##### m_replaceField

            EnvironmentField m_replaceField

      - ##### m_replacer

            SubstringReplacer m_replacer

      - ##### m_tempEditor

            PropertySheetPanel m_tempEditor

      - ##### m_upBut

            JButton m_upBut

  - ### Class weka.gui.beans.SubstringReplacerRules

    class SubstringReplacerRules extends Object implements Serializable
    serialVersionUID:
      -7151320452496749698L

    - #### Serialized Fields

      - ##### m_inputStructure

            Instances m_inputStructure

        The input structure

      - ##### m_matchRules

            List<SubstringReplacerRules.SubstringReplacerMatchRule> m_matchRules

      - ##### m_outputStructure

            Instances m_outputStructure

        The output structure

      - ##### m_statusMessagePrefix

            String m_statusMessagePrefix

        An optional prefix for status log messages

  - ### Class weka.gui.beans.SubstringReplacerRules.SubstringReplacerMatchRule

    class SubstringReplacerMatchRule extends Object implements Serializable
    serialVersionUID:
      5792838913737819728L

    - #### Serialized Fields

      - ##### m_attsToApplyTo

            String m_attsToApplyTo

        The attributes to apply the match-replace rule to

      - ##### m_ignoreCase

            boolean m_ignoreCase

        True if case should be ignored when matching

      - ##### m_logger

            Logger m_logger

      - ##### m_match

            String m_match

        The substring literal/regex to use for matching

      - ##### m_matchS

            String m_matchS

      - ##### m_regex

            boolean m_regex

        True if a regular expression match is to be used

      - ##### m_regexPattern

            Pattern m_regexPattern

        Precompiled regex

      - ##### m_replace

            String m_replace

        The string to replace with

      - ##### m_replaceS

            String m_replaceS

      - ##### m_selectedAtts

            int[] m_selectedAtts

      - ##### m_statusMessagePrefix

            String m_statusMessagePrefix

  - ### Class weka.gui.beans.TestSetEvent

    class TestSetEvent extends EventObject implements Serializable
    serialVersionUID:
      8780718708498854231L

    - #### Serialized Fields

      - ##### m_maxRunNumber

            int m_maxRunNumber

        Maximum number of runs.

      - ##### m_maxSetNumber

            int m_maxSetNumber

        Maximum number of sets (ie 10 in a 10 fold)

      - ##### m_runNumber

            int m_runNumber

        What run number is this training set from.

      - ##### m_setNumber

            int m_setNumber

        what number is this test set (ie fold 2 of 10 folds)

      - ##### m_structureOnly

            boolean m_structureOnly

      - ##### m_testSet

            Instances m_testSet

        The test set instances

  - ### Class weka.gui.beans.TestSetMaker

    class TestSetMaker extends AbstractTestSetProducer implements Serializable
    serialVersionUID:
      -8473882857628061841L

    - #### Serialized Fields

      - ##### m_receivedStopNotification

            boolean m_receivedStopNotification

  - ### Class weka.gui.beans.TextEvent

    class TextEvent extends EventObject implements Serializable
    serialVersionUID:
      4196810607402973744L

    - #### Serialized Fields

      - ##### m_text

            String m_text

        The text

      - ##### m_textTitle

            String m_textTitle

        The title for the text. Could be used in a list component

  - ### Class weka.gui.beans.TextSaver

    class TextSaver extends JPanel implements Serializable
    serialVersionUID:
      6363577506969809332L

    - #### Serialized Fields

      - ##### m_append

            boolean m_append

        Whether to append to the file or not

      - ##### m_fileName

            String m_fileName

        The file to save to

      - ##### m_visual

            BeanVisual m_visual

        Default visual for data sources

  - ### Class weka.gui.beans.TextSaverCustomizer

    class TextSaverCustomizer extends JPanel implements Serializable
    serialVersionUID:
      -1012433373647714743L

    - #### Serialized Fields

      - ##### m_append

            JCheckBox m_append

      - ##### m_env

            Environment m_env

      - ##### m_fileBackup

            String m_fileBackup

      - ##### m_fileEditor

            FileEnvironmentField m_fileEditor

      - ##### m_modifyListener

            BeanCustomizer.ModifyListener m_modifyListener

      - ##### m_parent

            Window m_parent

      - ##### m_textSaver

            TextSaver m_textSaver

  - ### Class weka.gui.beans.TextViewer

    class TextViewer extends JPanel implements Serializable
    serialVersionUID:
      104838186352536832L

    - #### Serialized Fields

      - ##### m_bcSupport

            BeanContextChildSupport m_bcSupport

        BeanContextChild support

      - ##### m_design

            boolean m_design

        True if this bean's appearance is the design mode appearance

      - ##### m_headlessEvents

            List<EventObject> m_headlessEvents

      - ##### m_textListeners

            Vector<TextListener> m_textListeners

        Objects listening for text events

      - ##### m_visual

            BeanVisual m_visual

  - ### Class weka.gui.beans.ThresholdDataEvent

    class ThresholdDataEvent extends EventObject implements Serializable
    serialVersionUID:
      -8309334224492439644L

    - #### Serialized Fields

      - ##### m_classAttribute

            Attribute m_classAttribute

      - ##### m_dataSet

            PlotData2D m_dataSet

  - ### Class weka.gui.beans.TrainingSetEvent

    class TrainingSetEvent extends EventObject implements Serializable
    serialVersionUID:
      5872343811810872662L

    - #### Serialized Fields

      - ##### m_maxRunNumber

            int m_maxRunNumber

        Maximum number of runs.

      - ##### m_maxSetNumber

            int m_maxSetNumber

        Maximum number of sets (ie 10 in a 10 fold)

      - ##### m_runNumber

            int m_runNumber

        What run number is this training set from.

      - ##### m_setNumber

            int m_setNumber

        what number is this training set (ie fold 2 of 10 folds)

      - ##### m_structureOnly

            boolean m_structureOnly

      - ##### m_trainingSet

            Instances m_trainingSet

        The training instances

  - ### Class weka.gui.beans.TrainingSetMaker

    class TrainingSetMaker extends AbstractTrainingSetProducer implements Serializable
    serialVersionUID:
      -6152577265471535786L

    - #### Serialized Fields

      - ##### m_receivedStopNotification

            boolean m_receivedStopNotification

  - ### Class weka.gui.beans.TrainTestSplitMaker

    class TrainTestSplitMaker extends AbstractTrainAndTestSetProducer implements Serializable
    serialVersionUID:
      7390064039444605943L

    - #### Serialized Fields

      - ##### m_dataProvider

            boolean m_dataProvider

      - ##### m_randomSeed

            int m_randomSeed

      - ##### m_splitThread

            Thread m_splitThread

      - ##### m_testProvider

            boolean m_testProvider

      - ##### m_trainingProvider

            boolean m_trainingProvider

      - ##### m_trainPercentage

            double m_trainPercentage

  - ### Class weka.gui.beans.TrainTestSplitMakerCustomizer

    class TrainTestSplitMakerCustomizer extends JPanel implements Serializable
    serialVersionUID:
      -1684662340241807260L

    - #### Serialized Fields

      - ##### m_pcSupport

            PropertyChangeSupport m_pcSupport

      - ##### m_splitEditor

            PropertySheetPanel m_splitEditor

  - ### Class weka.gui.beans.VisualizableErrorEvent

    class VisualizableErrorEvent extends EventObject implements Serializable
    serialVersionUID:
      -5811819270887223400L

    - #### Serialized Fields

      - ##### m_dataSet

            PlotData2D m_dataSet

- ## Package weka.gui.boundaryvisualizer

  - ### Class weka.gui.boundaryvisualizer.BoundaryPanel

    class BoundaryPanel extends JPanel implements Serializable
    serialVersionUID:
      -8499445518744770458L

    - #### Serialized Fields

      - ##### m_classifier

            Classifier m_classifier

        distribution classifier to use

      - ##### m_classIndex

            int m_classIndex

        index of the class attribute

      - ##### m_Colors

            ArrayList<Color> m_Colors

      - ##### m_dataGenerator

            DataGenerator m_dataGenerator

        data generator to use

      - ##### m_dummy

            Double m_dummy

      - ##### m_initialTiling

            boolean m_initialTiling

        is the main plot thread performing the initial coarse tiling

      - ##### m_listeners

            Vector<ActionListener> m_listeners

        listeners to be notified when plot is complete

      - ##### m_maxX

            double m_maxX

      - ##### m_maxY

            double m_maxY

      - ##### m_minX

            double m_minX

      - ##### m_minY

            double m_minY

      - ##### m_numOfSamplesPerGenerator

            int m_numOfSamplesPerGenerator

      - ##### m_numOfSamplesPerRegion

            int m_numOfSamplesPerRegion

      - ##### m_osi

            Image m_osi

        used for offscreen drawing

      - ##### m_panelHeight

            int m_panelHeight

      - ##### m_panelWidth

            int m_panelWidth

      - ##### m_pausePlotting

            boolean m_pausePlotting

      - ##### m_pixHeight

            double m_pixHeight

      - ##### m_pixWidth

            double m_pixWidth

      - ##### m_plotPanel

            weka.gui.boundaryvisualizer.BoundaryPanel.PlotPanel m_plotPanel

        the actual plotting area

      - ##### m_plotThread

            Thread m_plotThread

        thread for running the plotting operation in

      - ##### m_plotTrainingData

            boolean m_plotTrainingData

        plot the training data

      - ##### m_probabilityCache

            double[][][] m_probabilityCache

        cache of probabilities for fast replotting

      - ##### m_random

            Random m_random

        A random number generator

      - ##### m_rangeX

            double m_rangeX

      - ##### m_rangeY

            double m_rangeY

      - ##### m_samplesBase

            double m_samplesBase

      - ##### m_size

            int m_size

        what size of tile is currently being plotted

      - ##### m_stopPlotting

            boolean m_stopPlotting

        Stop the plotting thread

      - ##### m_stopReplotting

            boolean m_stopReplotting

        Stop any replotting threads

      - ##### m_trainingData

            Instances m_trainingData

        training data

      - ##### m_xAttribute

            int m_xAttribute

      - ##### m_yAttribute

            int m_yAttribute

  - ### Class weka.gui.boundaryvisualizer.BoundaryPanelDistributed

    class BoundaryPanelDistributed extends BoundaryPanel implements Serializable
    serialVersionUID:
      -1743284397893937776L

    - #### Serialized Fields

      - ##### m_failedCount

            int m_failedCount

        The count of failed sub-tasks

      - ##### m_hostPollingTime

            int[] m_hostPollingTime

      - ##### m_listeners

            Vector<RemoteExperimentListener> m_listeners

        a list of RemoteExperimentListeners

      - ##### m_minTaskPollTime

            int m_minTaskPollTime

        number of seconds between polling server

      - ##### m_plottingAborted

            boolean m_plottingAborted

        Set to true if MAX_FAILURES exceeded on all hosts or connections fail on all hosts or user aborts plotting

      - ##### m_remoteHostFailureCounts

            int[] m_remoteHostFailureCounts

        The number of times tasks have failed on each remote host

      - ##### m_remoteHosts

            Vector<String> m_remoteHosts

        Holds the names of machines with remoteEngine servers running

      - ##### m_remoteHostsQueue

            Queue m_remoteHostsQueue

        The queue of available hosts

      - ##### m_remoteHostsStatus

            int[] m_remoteHostsStatus

        The status of each of the remote hosts

      - ##### m_removedHosts

            int m_removedHosts

        The number of hosts removed due to exceeding max failures

      - ##### m_subExpQueue

            Queue m_subExpQueue

        The queue of sub-tasks waiting to be processed

  - ### Class weka.gui.boundaryvisualizer.BoundaryVisualizer

    class BoundaryVisualizer extends JPanel implements Serializable
    serialVersionUID:
      3933877580074013208L

    - #### Serialized Fields

      - ##### chooseButton

            JButton chooseButton

      - ##### COMBO_SIZE

            Dimension COMBO_SIZE

      - ##### dataFileLabel

            JLabel dataFileLabel

      - ##### m_addPointsButton

            JRadioButton m_addPointsButton

      - ##### m_addRemovePointsButtonGroup

            ButtonGroup m_addRemovePointsButtonGroup

      - ##### m_addRemovePointsPanel

            JPanel m_addRemovePointsPanel

      - ##### m_arffFileFilter

            ExtensionFileFilter m_arffFileFilter

      - ##### m_boundaryPanel

            BoundaryPanel m_boundaryPanel

        the plotting panel

      - ##### m_classAttBox

            JComboBox m_classAttBox

      - ##### m_classifier

            Classifier m_classifier

        the classifier to use

      - ##### m_classifierEditor

            GenericObjectEditor m_classifierEditor

      - ##### m_ClassifierPanel

            PropertyPanel m_ClassifierPanel

      - ##### m_classPanel

            ClassPanel m_classPanel

      - ##### m_classValueSelector

            JComboBox m_classValueSelector

      - ##### m_controlPanel

            JPanel m_controlPanel

      - ##### m_dataGenerator

            KDDataGenerator m_dataGenerator

      - ##### m_FileChooser

            WekaFileChooser m_FileChooser

        The file chooser for selecting arff files

      - ##### m_generatorSamplesBase

            int m_generatorSamplesBase

        base for sampling in the non-fixed dimensions

      - ##### m_generatorSamplesText

            JTextField m_generatorSamplesText

      - ##### m_kernelBandwidth

            int m_kernelBandwidth

        Set the kernel bandwidth to cover this many nearest neighbours

      - ##### m_kernelBandwidthText

            JTextField m_kernelBandwidthText

      - ##### m_maxX

            double m_maxX

      - ##### m_maxY

            double m_maxY

      - ##### m_minX

            double m_minX

      - ##### m_minY

            double m_minY

      - ##### m_numberOfSamplesFromEachRegion

            int m_numberOfSamplesFromEachRegion

      - ##### m_plotAreaHeight

            int m_plotAreaHeight

      - ##### m_plotAreaWidth

            int m_plotAreaWidth

      - ##### m_plotTrainingData

            JCheckBox m_plotTrainingData

      - ##### m_regionSamplesText

            JTextField m_regionSamplesText

      - ##### m_removePointsButton

            JRadioButton m_removePointsButton

      - ##### m_startBut

            JButton m_startBut

      - ##### m_trainingInstances

            Instances m_trainingInstances

        the training instances

      - ##### m_xAttBox

            JComboBox m_xAttBox

      - ##### m_xAxisPanel

            weka.gui.boundaryvisualizer.BoundaryVisualizer.AxisPanel m_xAxisPanel

      - ##### m_xIndex

            int m_xIndex

      - ##### m_yAttBox

            JComboBox m_yAttBox

      - ##### m_yAxisPanel

            weka.gui.boundaryvisualizer.BoundaryVisualizer.AxisPanel m_yAxisPanel

      - ##### m_yIndex

            int m_yIndex

      - ##### removeAllButton

            JButton removeAllButton

  - ### Class weka.gui.boundaryvisualizer.KDDataGenerator

    class KDDataGenerator extends Object implements Serializable
    serialVersionUID:
      -958573275606402792L

    - #### Serialized Fields

      - ##### m_globalMeansOrModes

            double[] m_globalMeansOrModes

        global means or modes to use for missing values

      - ##### m_instances

            Instances m_instances

        the instances to use

      - ##### m_kernelBandwidth

            int m_kernelBandwidth

        Number of neighbours to use for kernel bandwidth

      - ##### m_kernelParams

            double[][] m_kernelParams

        standard deviations for numeric attributes computed from the m_kernelBandwidth nearest neighbours for each kernel.

      - ##### m_laplaceConst

            double m_laplaceConst

        Laplace correction for discrete distributions

      - ##### m_Max

            double[] m_Max

        The maximum values for numeric attributes.

      - ##### m_Min

            double[] m_Min

        The minimum values for numeric attributes.

      - ##### m_random

            Random m_random

        random number generator

      - ##### m_seed

            int m_seed

        random number seed

      - ##### m_weightingDimensions

            boolean[] m_weightingDimensions

        which dimensions to use for computing a weight for each generated instance

      - ##### m_weightingValues

            double[] m_weightingValues

        the values for the weighting dimensions to use for computing the weight for the next instance to be generated

  - ### Class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask

    class RemoteBoundaryVisualizerSubTask extends Object implements Serializable
    serialVersionUID:
      -5275252329449241592L

    - #### Serialized Fields

      - ##### m_attsToWeightOn

            boolean[] m_attsToWeightOn

      - ##### m_classifier

            Classifier m_classifier

      - ##### m_dataGenerator

            DataGenerator m_dataGenerator

      - ##### m_dist

            double[] m_dist

      - ##### m_minX

            double m_minX

      - ##### m_minY

            double m_minY

      - ##### m_numOfSamplesPerGenerator

            int m_numOfSamplesPerGenerator

      - ##### m_numOfSamplesPerRegion

            int m_numOfSamplesPerRegion

      - ##### m_panelHeight

            int m_panelHeight

      - ##### m_panelWidth

            int m_panelWidth

      - ##### m_pixHeight

            double m_pixHeight

      - ##### m_pixWidth

            double m_pixWidth

      - ##### m_predInst

            Instance m_predInst

      - ##### m_random

            Random m_random

      - ##### m_result

            RemoteResult m_result

      - ##### m_rowNumber

            int m_rowNumber

      - ##### m_samplesBase

            double m_samplesBase

      - ##### m_status

            TaskStatusInfo m_status

      - ##### m_trainingData

            Instances m_trainingData

      - ##### m_vals

            double[] m_vals

      - ##### m_weightingAttsValues

            double[] m_weightingAttsValues

      - ##### m_xAttribute

            int m_xAttribute

      - ##### m_yAttribute

            int m_yAttribute

  - ### Class weka.gui.boundaryvisualizer.RemoteResult

    class RemoteResult extends Object implements Serializable
    serialVersionUID:
      1873271280044633808L

    - #### Serialized Fields

      - ##### m_percentCompleted

            int m_percentCompleted

        progress on computing this row

      - ##### m_probabilities

            double[][] m_probabilities

        the result - ie. the probability distributions produced by the classifier for this row in the visualization

- ## Package weka.gui.experiment

  - ### Class weka.gui.experiment.AbstractSetupPanel

    class AbstractSetupPanel extends JPanel implements Serializable

  - ### Class weka.gui.experiment.AlgorithmListPanel

    class AlgorithmListPanel extends JPanel implements Serializable
    serialVersionUID:
      -7204528834764898671L

    - #### Serialized Fields

      - ##### m_ActionListener

            ActionListener m_ActionListener

        An action listener that needs to be available globally to permit garbage collection.

      - ##### m_AddBut

            JButton m_AddBut

        Click to add an algorithm

      - ##### m_AlgorithmListModel

            DefaultListModel m_AlgorithmListModel

        The list model used

      - ##### m_ClassifierEditor

            GenericObjectEditor m_ClassifierEditor

        Lets the user configure the classifier

      - ##### m_DeleteBut

            JButton m_DeleteBut

        Click to remove the selected dataset from the list

      - ##### m_DownBut

            JButton m_DownBut

        Click to move the selected algorithm(s) one down

      - ##### m_EditBut

            JButton m_EditBut

        Click to edit the selected algorithm

      - ##### m_Editing

            boolean m_Editing

        Whether an algorithm is added or only edited

      - ##### m_Exp

            Experiment m_Exp

        The experiment to set the algorithm list of

      - ##### m_FileChooser

            WekaFileChooser m_FileChooser

        The file chooser for selecting experiments

      - ##### m_List

            JList<Classifier> m_List

        The component displaying the algorithm list

      - ##### m_LoadOptionsBut

            JButton m_LoadOptionsBut

        Click to edit the load the options for athe selected algorithm

      - ##### m_PD

            PropertyDialog m_PD

        The currently displayed property dialog, if any

      - ##### m_PropertyChangeListener

            PropertyChangeListener m_PropertyChangeListener

        An property change listener that needs to be available globally to permit garbage collection.

      - ##### m_SaveOptionsBut

            JButton m_SaveOptionsBut

        Click to edit the save the options from selected algorithm

      - ##### m_UpBut

            JButton m_UpBut

        Click to move the selected algorithm(s) one up

      - ##### m_XMLFilter

            FileFilter m_XMLFilter

        A filter to ensure only experiment (in XML format) files get shown in the chooser

  - ### Class weka.gui.experiment.AlgorithmListPanel.ObjectCellRenderer

    class ObjectCellRenderer extends DefaultListCellRenderer implements Serializable
    serialVersionUID:
      -5067138526587433808L

  - ### Class weka.gui.experiment.DatasetListPanel

    class DatasetListPanel extends JPanel implements Serializable
    serialVersionUID:
      7068857852794405769L

    - #### Serialized Fields

      - ##### m_AddBut

            JButton m_AddBut

        Click to add a dataset.

      - ##### m_DeleteBut

            JButton m_DeleteBut

        Click to remove the selected dataset from the list.

      - ##### m_DownBut

            JButton m_DownBut

        Click to move the selected dataset(s) one down.

      - ##### m_EditBut

            JButton m_EditBut

        Click to edit the selected algorithm.

      - ##### m_Exp

            Experiment m_Exp

        The experiment to set the dataset list of.

      - ##### m_FileChooser

            ConverterFileChooser m_FileChooser

        The file chooser component.

      - ##### m_List

            JList m_List

        The component displaying the dataset list.

      - ##### m_relativeCheck

            JCheckBox m_relativeCheck

        Make file paths relative to the user (start) directory.

      - ##### m_UpBut

            JButton m_UpBut

        Click to move the selected dataset(s) one up.

  - ### Class weka.gui.experiment.DistributeExperimentPanel

    class DistributeExperimentPanel extends JPanel implements Serializable
    serialVersionUID:
      5206721431754800278L

    - #### Serialized Fields

      - ##### m_configureHostNames

            JButton m_configureHostNames

        Popup the HostListPanel

      - ##### m_enableDistributedExperiment

            JCheckBox m_enableDistributedExperiment

        Distribute the current experiment to remote hosts

      - ##### m_Exp

            RemoteExperiment m_Exp

        The experiment to configure.

      - ##### m_hostList

            HostListPanel m_hostList

        The host list panel

      - ##### m_radioListener

            ActionListener m_radioListener

        Handle radio buttons

      - ##### m_splitByDataSet

            JRadioButton m_splitByDataSet

        Split experiment up by data set.

      - ##### m_splitByProperty

            JRadioButton m_splitByProperty

        Split experiment up by algorithm.

      - ##### m_splitByRun

            JRadioButton m_splitByRun

        Split experiment up by run number.

  - ### Class weka.gui.experiment.Experimenter

    class Experimenter extends AbstractPerspective implements Serializable
    serialVersionUID:
      -5751617505738193788L

    - #### Serialized Fields

      - ##### m_ClassFirst

            boolean m_ClassFirst

        True if the class attribute is the first attribute for all datasets involved in this experiment.

      - ##### m_ResultsPanel

            ResultsPanel m_ResultsPanel

        The panel for analysing experimental results

      - ##### m_RunPanel

            RunPanel m_RunPanel

        The panel for running the experiment

      - ##### m_SetupPanel

            SetupModePanel m_SetupPanel

        The panel for configuring the experiment

      - ##### m_TabbedPane

            JTabbedPane m_TabbedPane

        The tabbed pane that controls which sub-pane we are working with

  - ### Class weka.gui.experiment.ExperimenterDefaults

    class ExperimenterDefaults extends Object implements Serializable
    serialVersionUID:
      -2835933184632147981L

  - ### Class weka.gui.experiment.GeneratorPropertyIteratorPanel

    class GeneratorPropertyIteratorPanel extends JPanel implements Serializable
    serialVersionUID:
      -6026938995241632139L

    - #### Serialized Fields

      - ##### m_ArrayEditor

            GenericArrayEditor m_ArrayEditor

        Allows editing of the custom property values

      - ##### m_ConfigureBut

            JButton m_ConfigureBut

        Click to select the property to iterate over

      - ##### m_Exp

            Experiment m_Exp

        The experiment this all applies to

      - ##### m_Listeners

            ArrayList<ActionListener> m_Listeners

        Listeners who want to be notified about editing status of this panel

      - ##### m_StatusBox

            JComboBox m_StatusBox

        Controls whether the custom iterator is used or not

  - ### Class weka.gui.experiment.HostListPanel

    class HostListPanel extends JPanel implements Serializable
    serialVersionUID:
      7182791134585882197L

    - #### Serialized Fields

      - ##### m_DeleteBut

            JButton m_DeleteBut

        Click to remove the selected host from the list

      - ##### m_Exp

            RemoteExperiment m_Exp

        The remote experiment to set the host list of

      - ##### m_HostField

            JTextField m_HostField

        The field with which to enter host names

      - ##### m_List

            JList m_List

        The component displaying the host list

  - ### Class weka.gui.experiment.OutputFormatDialog

    class OutputFormatDialog extends JDialog implements Serializable
    serialVersionUID:
      2169792738187807378L

    - #### Serialized Fields

      - ##### m_CancelButton

            JButton m_CancelButton

        Click to cancel the dialog.

      - ##### m_IgnoreChanges

            boolean m_IgnoreChanges

        whether to ignore updates in the GUI momentarily.

      - ##### m_MeanPrecLabel

            JLabel m_MeanPrecLabel

        the label for the mean precision.

      - ##### m_MeanPrecSpinner

            JSpinner m_MeanPrecSpinner

        the spinner to choose the precision for the mean from.

      - ##### m_OkButton

            JButton m_OkButton

        Click to activate the current set parameters.

      - ##### m_OutputFormatClasses

            Vector<Class<?>> m_OutputFormatClasses

        the different classes for outputting the comparison tables.

      - ##### m_OutputFormatComboBox

            JComboBox m_OutputFormatComboBox

        lets the user choose the format for the output.

      - ##### m_OutputFormatLabel

            JLabel m_OutputFormatLabel

        the label for the format.

      - ##### m_OutputFormatNames

            Vector<String> m_OutputFormatNames

        the different names of matrices for outputting the comparison tables.

      - ##### m_RemoveFilterNameCheckBox

            JCheckBox m_RemoveFilterNameCheckBox

        the checkbox for the removing of filter classnames.

      - ##### m_RemoveFilterNameLabel

            JLabel m_RemoveFilterNameLabel

        the label for the removing the filter classnames.

      - ##### m_Result

            int m_Result

        the result of the user's action, either OK or CANCEL.

      - ##### m_ResultMatrix

            ResultMatrix m_ResultMatrix

        the current result matrix.

      - ##### m_ResultMatrixEditor

            GenericObjectEditor m_ResultMatrixEditor

        Lets the user configure the result matrix.

      - ##### m_ResultMatrixLabel

            JLabel m_ResultMatrixLabel

        the label for the GOE.

      - ##### m_ResultMatrixPanel

            PropertyPanel m_ResultMatrixPanel

        the panel for the GOE.

      - ##### m_ShowAverageCheckBox

            JCheckBox m_ShowAverageCheckBox

        the checkbox for outputting the average.

      - ##### m_ShowAverageLabel

            JLabel m_ShowAverageLabel

        the label for showing the average.

      - ##### m_StdDevPrecLabel

            JLabel m_StdDevPrecLabel

        the label for the std dev precision.

      - ##### m_StdDevPrecSpinner

            JSpinner m_StdDevPrecSpinner

        the spinner to choose the precision for the std. deviation from

  - ### Class weka.gui.experiment.ResultsPanel

    class ResultsPanel extends JPanel implements Serializable
    serialVersionUID:
      -4913007978534178569L

    - #### Serialized Fields

      - ##### COMBO_SIZE

            Dimension COMBO_SIZE

        the size for a combobox.

      - ##### m_arffFileFilter

            ExtensionFileFilter m_arffFileFilter

        ARFF file filter.

      - ##### m_CompareCombo

            JComboBox m_CompareCombo

        Lets the user select which performance measure to analyze.

      - ##### m_CompareModel

            DefaultComboBoxModel m_CompareModel

        The model embedded in m_CompareCombo.

      - ##### m_csvFileFilter

            ExtensionFileFilter m_csvFileFilter

        CSV file filter.

      - ##### m_DatasetAndResultKeysLabel

            JLabel m_DatasetAndResultKeysLabel

        Label for the dataset and result key buttons.

      - ##### m_DatasetKeyBut

            JButton m_DatasetKeyBut

        Click to edit the columns used to determine the scheme.

      - ##### m_DatasetKeyList

            JList m_DatasetKeyList

        Displays the list of selected columns determining the scheme.

      - ##### m_DatasetKeyModel

            DefaultListModel m_DatasetKeyModel

        Stores the list of attributes for selecting the scheme columns.

      - ##### m_DatasetModel

            DefaultComboBoxModel m_DatasetModel

        The model embedded in m_DatasetCombo.

      - ##### m_DisplayedButton

            JButton m_DisplayedButton

        Lets the user select which schemes are compared to base.

      - ##### m_DisplayedList

            JList m_DisplayedList

        Holds the list of schemes to display.

      - ##### m_DisplayedModel

            DefaultListModel m_DisplayedModel

        The model embedded in m_DisplayedList.

      - ##### m_Exp

            Experiment m_Exp

        An experiment (used for identifying a result source) -- optional.

      - ##### m_Explorer

            JButton m_Explorer

        Click to load the results instances into the Explorer

      - ##### m_FileChooser

            WekaFileChooser m_FileChooser

        The file chooser for selecting result files.

      - ##### m_FromDBaseBut

            JButton m_FromDBaseBut

        Click to load results from a database.

      - ##### m_FromExpBut

            JButton m_FromExpBut

        Click to get results from the destination given in the experiment.

      - ##### m_FromFileBut

            JButton m_FromFileBut

        Click to load results from a file.

      - ##### m_FromLab

            JLabel m_FromLab

        Displays a message about the current result set.

      - ##### m_History

            ResultHistoryPanel m_History

        A panel controlling results viewing.

      - ##### m_InstanceQuery

            InstanceQuery m_InstanceQuery

        Does any database querying for us.

      - ##### m_Instances

            Instances m_Instances

        The instances we're extracting results from.

      - ##### m_LoadThread

            Thread m_LoadThread

        A thread to load results instances from a file or database.

      - ##### m_mainPerspective

            Perspective m_mainPerspective

        If running in the Workbench (or other `GUIApplication`) this will hold a reference to the main perspective. Otherwise it will be null

      - ##### m_OutputFormatButton

            JButton m_OutputFormatButton

        lets the user choose the format for the output.

      - ##### m_OutText

            JTextArea m_OutText

        Displays the output of tests.

      - ##### m_PanelDatasetResultKeys

            JPanel m_PanelDatasetResultKeys

        the panel encapsulating the Rows/Columns/Swap buttons.

      - ##### m_PerformBut

            JButton m_PerformBut

        Click to start the test.

      - ##### m_ResultKeyBut

            JButton m_ResultKeyBut

        Click to edit the columns used to determine the scheme.

      - ##### m_ResultKeyList

            JList m_ResultKeyList

        Displays the list of selected columns determining the scheme.

      - ##### m_ResultKeyModel

            DefaultListModel m_ResultKeyModel

        Stores the list of attributes for selecting the scheme columns.

      - ##### m_ResultMatrix

            ResultMatrix m_ResultMatrix

        the initial result matrix.

      - ##### m_SaveOut

            SaveBuffer m_SaveOut

        The buffer saving object for saving output.

      - ##### m_SaveOutBut

            JButton m_SaveOutBut

        Click to save test output to a file.

      - ##### m_ShowStdDevs

            JCheckBox m_ShowStdDevs

        Lets the user select whether standard deviations are to be output or not.

      - ##### m_SigTex

            JTextField m_SigTex

        Lets the user edit the test significance.

      - ##### m_SortCombo

            JComboBox m_SortCombo

        Lets the user select which column to use for sorting.

      - ##### m_SortModel

            DefaultComboBoxModel m_SortModel

        The model embedded in m_SortCombo.

      - ##### m_SwapDatasetKeyAndResultKeyBut

            JButton m_SwapDatasetKeyAndResultKeyBut

        For swapping rows and columns.

      - ##### m_TesterClasses

            JComboBox m_TesterClasses

        Lists all the available classes implementing the Tester-Interface.
        See Also:
          - `Tester`

      - ##### m_TesterClassesLabel

            JLabel m_TesterClassesLabel

        Displays the currently selected Tester-Class.

      - ##### m_TesterClassesModel

            DefaultComboBoxModel m_TesterClassesModel

        Contains all the available classes implementing the Tester-Interface (the display names).
        See Also:
          - `Tester`

      - ##### m_TestsButton

            JButton m_TestsButton

        Lets the user select which scheme to base comparisons against.

      - ##### m_TestsList

            JList m_TestsList

        Holds the list of schemes to base the test against.

      - ##### m_TestsModel

            DefaultListModel m_TestsModel

        The model embedded in m_TestsList.

      - ##### m_TTester

            Tester m_TTester

        The PairedTTester object.

  - ### Class weka.gui.experiment.RunNumberPanel

    class RunNumberPanel extends JPanel implements Serializable
    serialVersionUID:
      -1644336658426067852L

    - #### Serialized Fields

      - ##### m_Exp

            Experiment m_Exp

        The experiment being configured

      - ##### m_LowerText

            JTextField m_LowerText

        Configures the lower run number

      - ##### m_UpperText

            JTextField m_UpperText

        Configures the upper run number

  - ### Class weka.gui.experiment.RunPanel

    class RunPanel extends JPanel implements Serializable
    serialVersionUID:
      1691868018596872051L

    - #### Serialized Fields

      - ##### m_Exp

            Experiment m_Exp

        The experiment to run

      - ##### m_Log

            LogPanel m_Log

      - ##### m_ResultsPanel

            ResultsPanel m_ResultsPanel

        A pointer to the results panel

      - ##### m_RunThread

            Thread m_RunThread

        The thread running the experiment

      - ##### m_StartBut

            JButton m_StartBut

        Click to start running the experiment

      - ##### m_StopBut

            JButton m_StopBut

        Click to signal the running experiment to halt

  - ### Class weka.gui.experiment.SetupModePanel

    class SetupModePanel extends JPanel implements Serializable
    serialVersionUID:
      -3758035565520727822L

    - #### Serialized Fields

      - ##### m_advancedPanel

            AbstractSetupPanel m_advancedPanel

        The advanced setup panel

      - ##### m_ComboBoxPanels

            JComboBox m_ComboBoxPanels

        the combobox with all available setup panels.

      - ##### m_CurrentPanel

            AbstractSetupPanel m_CurrentPanel

        the current panel.

      - ##### m_defaultPanel

            AbstractSetupPanel m_defaultPanel

        The simple setup panel

      - ##### m_Panels

            AbstractSetupPanel[] m_Panels

        the available panels.

  - ### Class weka.gui.experiment.SetupPanel

    class SetupPanel extends AbstractSetupPanel implements Serializable
    serialVersionUID:
      6552671886903170033L

    - #### Serialized Fields

      - ##### m_advanceDataSetFirst

            JRadioButton m_advanceDataSetFirst

        Click to advacne data set before custom generator

      - ##### m_advanceIteratorFirst

            JRadioButton m_advanceIteratorFirst

        Click to advance custom generator before data set

      - ##### m_DatasetListPanel

            DatasetListPanel m_DatasetListPanel

        The panel for configuring selected datasets

      - ##### m_DistributeExperimentPanel

            DistributeExperimentPanel m_DistributeExperimentPanel

        The panel for enabling a distributed experiment

      - ##### m_Exp

            Experiment m_Exp

        The experiment being configured

      - ##### m_ExpFilter

            FileFilter m_ExpFilter

        A filter to ensure only experiment files get shown in the chooser

      - ##### m_FileChooser

            WekaFileChooser m_FileChooser

        The file chooser for selecting experiments

      - ##### m_GeneratorPropertyPanel

            GeneratorPropertyIteratorPanel m_GeneratorPropertyPanel

        The panel that configures iteration on custom resultproducer property

      - ##### m_KOMLFilter

            FileFilter m_KOMLFilter

        A filter to ensure only experiment (in KOML format) files get shown in the chooser

      - ##### m_modePanel

            SetupModePanel m_modePanel

        The panel which switched between simple and advanced setup modes

      - ##### m_NewBut

            JButton m_NewBut

        Click to create a new experiment with default settings

      - ##### m_NotesButton

            JButton m_NotesButton

        A button for bringing up the notes

      - ##### m_NotesFrame

            JFrame m_NotesFrame

        Frame for the notes

      - ##### m_NotesText

            JTextArea m_NotesText

        Area for user notes Default of 10 rows

      - ##### m_OpenBut

            JButton m_OpenBut

        Click to load an experiment

      - ##### m_RadioListener

            ActionListener m_RadioListener

        Handle radio buttons

      - ##### m_RLEditor

            GenericObjectEditor m_RLEditor

        The ResultListener editor

      - ##### m_RLEditorPanel

            PropertyPanel m_RLEditorPanel

        The panel to contain the ResultListener editor

      - ##### m_RPEditor

            GenericObjectEditor m_RPEditor

        The ResultProducer editor

      - ##### m_RPEditorPanel

            PropertyPanel m_RPEditorPanel

        The panel to contain the ResultProducer editor

      - ##### m_RunNumberPanel

            RunNumberPanel m_RunNumberPanel

        The panel for configuring run numbers

      - ##### m_SaveBut

            JButton m_SaveBut

        Click to save an experiment

      - ##### m_Support

            PropertyChangeSupport m_Support

        Manages sending notifications to people when we change the experiment, at this stage, only the resultlistener so the resultpanel can update.

      - ##### m_XMLFilter

            FileFilter m_XMLFilter

        A filter to ensure only experiment (in XML format) files get shown in the chooser

  - ### Class weka.gui.experiment.SimpleSetupPanel

    class SimpleSetupPanel extends AbstractSetupPanel implements Serializable
    serialVersionUID:
      5257424515609176509L

    - #### Serialized Fields

      - ##### m_AlgorithmListPanel

            AlgorithmListPanel m_AlgorithmListPanel

        The panel for configuring selected algorithms

      - ##### m_arffFileFilter

            ExtensionFileFilter m_arffFileFilter

        FIlter for choosing ARFF files

      - ##### m_BrowseDestinationButton

            JButton m_BrowseDestinationButton

        Button for browsing destination files

      - ##### m_csvFileFilter

            ExtensionFileFilter m_csvFileFilter

        Filter for choosing CSV files

      - ##### m_DatasetListPanel

            DatasetListPanel m_DatasetListPanel

        The panel for configuring selected datasets

      - ##### m_DestFileChooser

            WekaFileChooser m_DestFileChooser

        The file chooser for selecting result destinations

      - ##### m_destinationDatabaseURL

            String m_destinationDatabaseURL

        The database destination URL to store results into

      - ##### m_destinationFilename

            String m_destinationFilename

        The filename to store results into

      - ##### m_Exp

            Experiment m_Exp

        The experiment being configured

      - ##### m_ExpClassificationRBut

            JRadioButton m_ExpClassificationRBut

        Radio button for choosing classification experiment

      - ##### m_ExperimentParameterLabel

            JLabel m_ExperimentParameterLabel

        Label for parameter field

      - ##### m_ExperimentParameterTField

            JTextField m_ExperimentParameterTField

        Input field for experiment parameter

      - ##### m_ExperimentTypeCBox

            JComboBox m_ExperimentTypeCBox

        Combo box for choosing experiment type

      - ##### m_ExpFilter

            FileFilter m_ExpFilter

        A filter to ensure only experiment files get shown in the chooser

      - ##### m_ExpRegressionRBut

            JRadioButton m_ExpRegressionRBut

        Radio button for choosing regression experiment

      - ##### m_FileChooser

            WekaFileChooser m_FileChooser

        The file chooser for selecting experiments

      - ##### m_KOMLFilter

            FileFilter m_KOMLFilter

        A filter to ensure only experiment (in KOML format) files get shown in the chooser

      - ##### m_modePanel

            SetupModePanel m_modePanel

        The panel which switched between simple and advanced setup modes

      - ##### m_NewBut

            JButton m_NewBut

        Click to create a new experiment with default settings

      - ##### m_NotesButton

            JButton m_NotesButton

        A button for bringing up the notes

      - ##### m_NotesFrame

            JFrame m_NotesFrame

        Frame for the notes

      - ##### m_NotesText

            JTextArea m_NotesText

        Area for user notes Default of 10 rows

      - ##### m_NumberOfRepetitionsTField

            JTextField m_NumberOfRepetitionsTField

        Input field for number of repetitions

      - ##### m_numFolds

            int m_numFolds

        The number of folds for a cross-validation experiment

      - ##### m_numRepetitions

            int m_numRepetitions

        The number of times to repeat the sub-experiment

      - ##### m_OpenBut

            JButton m_OpenBut

        Click to load an experiment

      - ##### m_OrderAlgorithmsFirstRBut

            JRadioButton m_OrderAlgorithmsFirstRBut

        Radio button for choosing algorithms first in order of execution

      - ##### m_OrderDatasetsFirstRBut

            JRadioButton m_OrderDatasetsFirstRBut

        Radio button for choosing datasets first in order of execution

      - ##### m_ResultsDestinationCBox

            JComboBox m_ResultsDestinationCBox

        Combo box for choosing experiment destination type

      - ##### m_ResultsDestinationPathLabel

            JLabel m_ResultsDestinationPathLabel

        Label for destination field

      - ##### m_ResultsDestinationPathTField

            JTextField m_ResultsDestinationPathTField

        Input field for result destination path

      - ##### m_SaveBut

            JButton m_SaveBut

        Click to save an experiment

      - ##### m_Support

            PropertyChangeSupport m_Support

        Manages sending notifications to people when we change the experiment, at this stage, only the resultlistener so the resultpanel can update.

      - ##### m_trainPercent

            double m_trainPercent

        The training percentage for a train/test split experiment

      - ##### m_userHasBeenAskedAboutConversion

            boolean m_userHasBeenAskedAboutConversion

        Whether or not the user has consented for the experiment to be simplified

      - ##### m_XMLFilter

            FileFilter m_XMLFilter

        A filter to ensure only experiment (in XML format) files get shown in the chooser

- ## Package weka.gui.explorer

  - ### Class weka.gui.explorer.AbstractPlotInstances

    class AbstractPlotInstances extends Object implements Serializable
    serialVersionUID:
      2375155184845160908L

    - #### Serialized Fields

      - ##### m_FinishUpCalled

            boolean m_FinishUpCalled

        whether processing has been finished up already.

      - ##### m_Instances

            Instances m_Instances

        the full dataset.

      - ##### m_PlotInstances

            Instances m_PlotInstances

        the plotable instances.

  - ### Class weka.gui.explorer.AssociationsPanel

    class AssociationsPanel extends AbstractPerspective implements Serializable
    serialVersionUID:
      -6867871711865476971L

    - #### Serialized Fields

      - ##### m_AssociatorEditor

            GenericObjectEditor m_AssociatorEditor

        Lets the user configure the associator

      - ##### m_CEPanel

            PropertyPanel m_CEPanel

        The panel showing the current associator selection

      - ##### m_Explorer

            Explorer m_Explorer

        the parent frame

      - ##### m_History

            ResultHistoryPanel m_History

        A panel controlling results viewing

      - ##### m_initialSettingsSet

            boolean m_initialSettingsSet

        Whether start-up settings have been applied (i.e. initial default associator to use

      - ##### m_Instances

            Instances m_Instances

        The main set of instances we're playing with

      - ##### m_Log

            Logger m_Log

        The destination for log/status messages

      - ##### m_OutText

            JTextArea m_OutText

        The output area for associations

      - ##### m_RunThread

            Thread m_RunThread

        A thread that associator runs in

      - ##### m_SaveOut

            SaveBuffer m_SaveOut

        The buffer saving object for saving output

      - ##### m_StartBut

            JButton m_StartBut

        Click to start running the associator

      - ##### m_StopBut

            JButton m_StopBut

        Click to stop a running associator

      - ##### m_storeOutput

            JCheckBox m_storeOutput

        Whether to store any graph or xml rules output in the history list

      - ##### m_TestInstances

            Instances m_TestInstances

        The user-supplied test set (if any)

  - ### Class weka.gui.explorer.AssociationsPanel.AssociationsPanelDefaults

    class AssociationsPanelDefaults extends Defaults implements Serializable
    serialVersionUID:
      1108450683775771792L

  - ### Class weka.gui.explorer.AttributeSelectionPanel

    class AttributeSelectionPanel extends AbstractPerspective implements Serializable
    serialVersionUID:
      5627185966993476142L

    - #### Serialized Fields

      - ##### COMBO_SIZE

            Dimension COMBO_SIZE

        Stop the class combo from taking up to much space

      - ##### m_AEEPanel

            PropertyPanel m_AEEPanel

        The panel showing the current attribute evaluation method

      - ##### m_ASEPanel

            PropertyPanel m_ASEPanel

        The panel showing the current search method

      - ##### m_AttributeEvaluatorEditor

            GenericObjectEditor m_AttributeEvaluatorEditor

        Lets the user configure the attribute evaluator

      - ##### m_AttributeSearchEditor

            GenericObjectEditor m_AttributeSearchEditor

        Lets the user configure the search method

      - ##### m_ClassCombo

            JComboBox m_ClassCombo

        Lets the user select the class column

      - ##### m_CVBut

            JRadioButton m_CVBut

        Click to set evaluation mode to cross-validation

      - ##### m_CVLab

            JLabel m_CVLab

        Label by where the cv folds are entered

      - ##### m_CVText

            JTextField m_CVText

        The field where the cv folds are entered

      - ##### m_Explorer

            Explorer m_Explorer

        the parent frame

      - ##### m_History

            ResultHistoryPanel m_History

        A panel controlling results viewing

      - ##### m_initialSettingsSet

            boolean m_initialSettingsSet

        True if startup settings have been applied

      - ##### m_Instances

            Instances m_Instances

        The main set of instances we're playing with

      - ##### m_Log

            Logger m_Log

        The destination for log/status messages

      - ##### m_OutText

            JTextArea m_OutText

        The output area for attribute selection results

      - ##### m_RadioListener

            ActionListener m_RadioListener

        Alters the enabled/disabled status of elements associated with each radio button

      - ##### m_RunThread

            Thread m_RunThread

        A thread that attribute selection runs in

      - ##### m_SaveOut

            SaveBuffer m_SaveOut

        The buffer saving object for saving output

      - ##### m_SeedLab

            JLabel m_SeedLab

        Label by where cv random seed is entered

      - ##### m_SeedText

            JTextField m_SeedText

        The field where the seed value is entered

      - ##### m_StartBut

            JButton m_StartBut

        Click to start running the attribute selector

      - ##### m_StopBut

            JButton m_StopBut

        Click to stop a running classifier

      - ##### m_TrainBut

            JRadioButton m_TrainBut

        Click to set test mode to test on training data

  - ### Class weka.gui.explorer.AttributeSelectionPanel.AttributeSelectionPanelDefaults

    class AttributeSelectionPanelDefaults extends Defaults implements Serializable
    serialVersionUID:
      -5413933415469545770L

  - ### Class weka.gui.explorer.ClassifierErrorsPlotInstances

    class ClassifierErrorsPlotInstances extends AbstractPlotInstances implements Serializable
    serialVersionUID:
      -3941976365792013279L

    - #### Serialized Fields

      - ##### m_Classifier

            Classifier m_Classifier

        the classifier being used.

      - ##### m_ClassIndex

            int m_ClassIndex

        the class index.

      - ##### m_Evaluation

            Evaluation m_Evaluation

        the Evaluation object to use.

      - ##### m_MaximumPlotSizeNumeric

            int m_MaximumPlotSizeNumeric

        the maximum plot size for numeric errors.

      - ##### m_MinimumPlotSizeNumeric

            int m_MinimumPlotSizeNumeric

        the minimum plot size for numeric errors.

      - ##### m_PlotShapes

            ArrayList<Integer> m_PlotShapes

        for storing the plot shapes.

      - ##### m_PlotSizes

            ArrayList<Object> m_PlotSizes

        for storing the plot sizes.

      - ##### m_pointSizeProportionalToMargin

            boolean m_pointSizeProportionalToMargin

      - ##### m_SaveForVisualization

            boolean m_SaveForVisualization

        whether to save the instances for visualization or just evaluate the instance.

  - ### Class weka.gui.explorer.ClassifierPanel

    class ClassifierPanel extends AbstractPerspective implements Serializable
    serialVersionUID:
      6959973704963624003L

    - #### Serialized Fields

      - ##### COMBO_SIZE

            Dimension COMBO_SIZE

        Stop the class combo from taking up to much space.

      - ##### m_CEPanel

            PropertyPanel m_CEPanel

        The panel showing the current classifier selection.

      - ##### m_ClassCombo

            JComboBox m_ClassCombo

        Lets the user select the class column.

      - ##### m_ClassificationOutputEditor

            GenericObjectEditor m_ClassificationOutputEditor

        Lets the user configure the ClassificationOutput.

      - ##### m_ClassificationOutputPanel

            PropertyPanel m_ClassificationOutputPanel

        ClassificationOutput configuration.

      - ##### m_ClassifierEditor

            GenericObjectEditor m_ClassifierEditor

        Lets the user configure the classifier.

      - ##### m_CollectPredictionsForEvaluationBut

            JCheckBox m_CollectPredictionsForEvaluationBut

        Check to collect the predictions for computing statistics such as AUROC.

      - ##### m_CostMatrixEditor

            CostMatrixEditor m_CostMatrixEditor

        The cost matrix editor for evaluation costs.

      - ##### m_CVBut

            JRadioButton m_CVBut

        Click to set test mode to cross-validation.

      - ##### m_CVLab

            JLabel m_CVLab

        Label by where the cv folds are entered.

      - ##### m_CVText

            JTextField m_CVText

        The field where the cv folds are entered.

      - ##### m_errorPlotPointSizeProportionalToMargin

            JCheckBox m_errorPlotPointSizeProportionalToMargin

        Check to have the point size in error plots proportional to the prediction margin (classification only)

      - ##### m_EvalWRTCostsBut

            JCheckBox m_EvalWRTCostsBut

        Check to evaluate w.r.t a cost matrix.

      - ##### m_Explorer

            Explorer m_Explorer

        the parent frame.

      - ##### m_FileChooser

            WekaFileChooser m_FileChooser

        The file chooser for selecting model files.

      - ##### m_History

            ResultHistoryPanel m_History

        A panel controlling results viewing.

      - ##### m_initialSettingsSet

            boolean m_initialSettingsSet

        Whether start-up settings have been applied (i.e. initial classifier to use)

      - ##### m_Instances

            Instances m_Instances

        The main set of instances we're playing with.

      - ##### m_Log

            Logger m_Log

        The destination for log/status messages.

      - ##### m_ModelFilter

            FileFilter m_ModelFilter

        Filter to ensure only model files are selected.

      - ##### m_MoreOptions

            JButton m_MoreOptions

        Button for further output/visualize options.

      - ##### m_OutputAdditionalAttributesRange

            Range m_OutputAdditionalAttributesRange

        the range of attributes to output.

      - ##### m_OutputConfusionBut

            JCheckBox m_OutputConfusionBut

        Check to output a confusion matrix.

      - ##### m_OutputEntropyBut

            JCheckBox m_OutputEntropyBut

        Check to output entropy statistics.

      - ##### m_OutputModelBut

            JCheckBox m_OutputModelBut

        Check to output the model built from the training data.

      - ##### m_OutputModelsForTrainingSplitsBut

            JCheckBox m_OutputModelsForTrainingSplitsBut

        Check to output the models built from the training splits.

      - ##### m_OutputPerClassBut

            JCheckBox m_OutputPerClassBut

        Check to output true/false positives, precision/recall for each class.

      - ##### m_OutputSourceCode

            JCheckBox m_OutputSourceCode

        Whether to output the source code (only for classifiers importing Sourcable).

      - ##### m_OutText

            JTextArea m_OutText

        The output area for classification results.

      - ##### m_PercentBut

            JRadioButton m_PercentBut

        Click to set test mode to generate a % split.

      - ##### m_PercentLab

            JLabel m_PercentLab

        Label by where the % split is entered.

      - ##### m_PercentText

            JTextField m_PercentText

        The field where the % split is entered.

      - ##### m_PMMLModelFilter

            FileFilter m_PMMLModelFilter

      - ##### m_PreserveOrderBut

            JCheckBox m_PreserveOrderBut

        Whether randomization is turned off to preserve order.

      - ##### m_RadioListener

            ActionListener m_RadioListener

        Alters the enabled/disabled status of elements associated with each radio button.

      - ##### m_RandomLab

            JLabel m_RandomLab

        the label for the random seed textfield.

      - ##### m_RandomSeedText

            JTextField m_RandomSeedText

        User specified random seed for cross validation or % split.

      - ##### m_RunThread

            Thread m_RunThread

        A thread that classification runs in.

      - ##### m_SaveOut

            SaveBuffer m_SaveOut

        The buffer saving object for saving output.

      - ##### m_selectedEvalMetrics

            List<String> m_selectedEvalMetrics

        The user's list of selected evaluation metrics

      - ##### m_SetCostsBut

            JButton m_SetCostsBut

        for the cost matrix.

      - ##### m_SetCostsFrame

            PropertyDialog m_SetCostsFrame

        The frame used to show the cost matrix editing panel.

      - ##### m_SetTestBut

            JButton m_SetTestBut

        The button used to open a separate test dataset.

      - ##### m_SetTestFrame

            JFrame m_SetTestFrame

        The frame used to show the test set selection panel.

      - ##### m_SourceCodeClass

            JTextField m_SourceCodeClass

        The name of the generated class (only applicable to Sourcable schemes).

      - ##### m_StartBut

            JButton m_StartBut

        Click to start running the classifier.

      - ##### m_StopBut

            JButton m_StopBut

        Click to stop a running classifier.

      - ##### m_StoreTestDataAndPredictionsBut

            JCheckBox m_StoreTestDataAndPredictionsBut

        Check to save the test data and the predictions in the results list for visualizing later on.

      - ##### m_TestClassIndex

            int m_TestClassIndex

        the class index for the supplied test set.

      - ##### m_TestLoader

            Loader m_TestLoader

        The loader used to load the user-supplied test set (if any).

      - ##### m_TestSplitBut

            JRadioButton m_TestSplitBut

        Click to set test mode to a user-specified test set.

      - ##### m_TrainBut

            JRadioButton m_TrainBut

        Click to set test mode to test on training data.

  - ### Class weka.gui.explorer.ClassifierPanel.ClassifierPanelDefaults

    class ClassifierPanelDefaults extends Defaults implements Serializable
    serialVersionUID:
      7109938811150596359L

  - ### Class weka.gui.explorer.ClustererAssignmentsPlotInstances

    class ClustererAssignmentsPlotInstances extends AbstractPlotInstances implements Serializable
    serialVersionUID:
      -4748134272046520423L

    - #### Serialized Fields

      - ##### m_Clusterer

            Clusterer m_Clusterer

        the clusterer being used.

      - ##### m_Evaluation

            ClusterEvaluation m_Evaluation

        the cluster evaluation to use.

      - ##### m_PlotShapes

            int[] m_PlotShapes

        for storing the plot shapes.

  - ### Class weka.gui.explorer.ClustererPanel

    class ClustererPanel extends AbstractPerspective implements Serializable
    serialVersionUID:
      -2474932792950820990L

    - #### Serialized Fields

      - ##### COMBO_SIZE

            Dimension COMBO_SIZE

        Stop the class combo from taking up to much space

      - ##### m_ClassCombo

            JComboBox m_ClassCombo

        Lets the user select the class column for classes to clusters based evaluation

      - ##### m_ClassesToClustersBut

            JRadioButton m_ClassesToClustersBut

        Click to set test mode to classes to clusters based evaluation

      - ##### m_CLPanel

            PropertyPanel m_CLPanel

        The panel showing the current clusterer selection

      - ##### m_ClustererEditor

            GenericObjectEditor m_ClustererEditor

        Lets the user configure the clusterer

      - ##### m_CurrentVis

            VisualizePanel m_CurrentVis

        The current visualization object

      - ##### m_Explorer

            Explorer m_Explorer

        the parent frame

      - ##### m_FileChooser

            WekaFileChooser m_FileChooser

        The file chooser for selecting model files

      - ##### m_History

            ResultHistoryPanel m_History

        A panel controlling results viewing

      - ##### m_ignoreBut

            JButton m_ignoreBut

        The button used to popup a list for choosing attributes to ignore while clustering

      - ##### m_ignoreKeyList

            JList m_ignoreKeyList

      - ##### m_ignoreKeyModel

            DefaultListModel m_ignoreKeyModel

      - ##### m_initialSettingsSet

            boolean m_initialSettingsSet

        Whether startup settings have been applied yet or not

      - ##### m_Instances

            Instances m_Instances

        The main set of instances we're playing with

      - ##### m_Log

            Logger m_Log

        The destination for log/status messages

      - ##### m_ModelFilter

            FileFilter m_ModelFilter

        Filter to ensure only model files are selected

      - ##### m_OutText

            JTextArea m_OutText

        The output area for classification results

      - ##### m_PercentBut

            JRadioButton m_PercentBut

        Click to set test mode to generate a % split

      - ##### m_PercentLab

            JLabel m_PercentLab

        Label by where the % split is entered

      - ##### m_PercentText

            JTextField m_PercentText

        The field where the % split is entered

      - ##### m_RadioListener

            ActionListener m_RadioListener

        Alters the enabled/disabled status of elements associated with each radio button

      - ##### m_RunThread

            Thread m_RunThread

        A thread that clustering runs in

      - ##### m_SaveOut

            SaveBuffer m_SaveOut

        The buffer saving object for saving output

      - ##### m_SetTestBut

            JButton m_SetTestBut

        The button used to open a separate test dataset

      - ##### m_SetTestFrame

            JFrame m_SetTestFrame

        The frame used to show the test set selection panel

      - ##### m_StartBut

            JButton m_StartBut

        Click to start running the clusterer

      - ##### m_StopBut

            JButton m_StopBut

        Click to stop a running clusterer

      - ##### m_StorePredictionsBut

            JCheckBox m_StorePredictionsBut

        Check to save the predictions in the results list for visualizing later on

      - ##### m_Summary

            InstancesSummaryPanel m_Summary

        The instances summary panel displayed by m_SetTestFrame

      - ##### m_TestInstances

            Instances m_TestInstances

        The user-supplied test set (if any)

      - ##### m_TestSplitBut

            JRadioButton m_TestSplitBut

        Click to set test mode to a user-specified test set

      - ##### m_TrainBut

            JRadioButton m_TrainBut

        Click to set test mode to test on training data

  - ### Class weka.gui.explorer.ClustererPanel.ClustererPanelDefaults

    class ClustererPanelDefaults extends Defaults implements Serializable
    serialVersionUID:
      2708388782229179493L

  - ### Class weka.gui.explorer.DataGeneratorPanel

    class DataGeneratorPanel extends JPanel implements Serializable
    serialVersionUID:
      -2520408165350629380L

    - #### Serialized Fields

      - ##### m_GeneratorEditor

            GenericObjectEditor m_GeneratorEditor

        the GOE for the generators

      - ##### m_Instances

            Instances m_Instances

        the generated Instances

      - ##### m_Log

            Logger m_Log

        The destination for log/status messages

      - ##### m_Output

            StringWriter m_Output

        the generated output (as text)

  - ### Class weka.gui.explorer.Explorer

    class Explorer extends JPanel implements Serializable
    serialVersionUID:
      -7674003708867909578L

    - #### Serialized Fields

      - ##### m_CapabilitiesFilterChangeListeners

            HashSet<Explorer.CapabilitiesFilterChangeListener> m_CapabilitiesFilterChangeListeners

        the listeners that listen to filter changes

      - ##### m_LogPanel

            LogPanel m_LogPanel

        The panel for log and status messages

      - ##### m_Panels

            Vector<Explorer.ExplorerPanel> m_Panels

        Contains all the additional panels apart from the pre-processing panel

      - ##### m_PreprocessPanel

            PreprocessPanel m_PreprocessPanel

        The panel for preprocessing instances

      - ##### m_TabbedPane

            JTabbedPane m_TabbedPane

        The tabbed pane that controls which sub-pane we are working with

  - ### Class weka.gui.explorer.Explorer.CapabilitiesFilterChangeEvent

    class CapabilitiesFilterChangeEvent extends ChangeEvent implements Serializable
    serialVersionUID:
      1194260517270385559L

    - #### Serialized Fields

      - ##### m_Filter

            Capabilities m_Filter

        the capabilities filter

  - ### Class weka.gui.explorer.ExplorerDefaults

    class ExplorerDefaults extends Object implements Serializable
    serialVersionUID:
      4954795757927524225L

  - ### Class weka.gui.explorer.PreprocessPanel

    class PreprocessPanel extends AbstractPerspective implements Serializable
    serialVersionUID:
      6764850273874813049L

    - #### Serialized Fields

      - ##### m_ApplyFilterBut

            JButton m_ApplyFilterBut

        Click to apply filters and save the results

      - ##### m_AttPanel

            AttributeSelectionPanel m_AttPanel

        Panel to let the user toggle attributes

      - ##### m_AttSummaryPanel

            AttributeSummaryPanel m_AttSummaryPanel

        Displays summary stats on the selected attribute

      - ##### m_AttVisualizePanel

            AttributeVisualizationPanel m_AttVisualizePanel

        The visualization of the attribute values

      - ##### m_DataGenerator

            DataGenerator m_DataGenerator

        The last generator that was selected

      - ##### m_EditBut

            JButton m_EditBut

        Click to open the current instances in a viewer

      - ##### m_EditM

            JMenuItem m_EditM

      - ##### m_Explorer

            Explorer m_Explorer

        the parent frame

      - ##### m_FileChooser

            ConverterFileChooser m_FileChooser

        The file chooser for selecting data files

      - ##### m_FilterEditor

            GenericObjectEditor m_FilterEditor

        Lets the user configure the filter

      - ##### m_FilterPanel

            PropertyPanel m_FilterPanel

        Filter configuration

      - ##### m_GenerateBut

            JButton m_GenerateBut

        Click to generate artificial data

      - ##### m_initialSettingsSet

            boolean m_initialSettingsSet

        True after settings have been applied the first time

      - ##### m_Instances

            Instances m_Instances

        The working instances

      - ##### m_InstSummaryPanel

            InstancesSummaryPanel m_InstSummaryPanel

        Displays simple stats on the working instances

      - ##### m_IOThread

            Thread m_IOThread

        A thread for loading/saving instances from a file or URL

      - ##### m_LastURL

            String m_LastURL

        Stores the last URL that instances were loaded from

      - ##### m_Log

            Logger m_Log

        The message logger

      - ##### m_menus

            List<JMenu> m_menus

        Menus provided by this perspective

      - ##### m_OpenDBBut

            JButton m_OpenDBBut

        Click to load base instances from a Database

      - ##### m_OpenFileBut

            JButton m_OpenFileBut

        Click to load base instances from a file

      - ##### m_OpenURLBut

            JButton m_OpenURLBut

        Click to load base instances from a URL

      - ##### m_RemoveButton

            JButton m_RemoveButton

        Button for removing attributes

      - ##### m_SaveBut

            JButton m_SaveBut

        Click to apply filters and save the results

      - ##### m_sendToPerspective

            JMenu m_sendToPerspective

        For sending instances to various perspectives/tabs

      - ##### m_SQLQ

            String m_SQLQ

        Stores the last sql query executed

      - ##### m_StopBut

            JButton m_StopBut

        Click to stop a running filter

      - ##### m_Support

            PropertyChangeSupport m_Support

        Manages sending notifications to people when we change the set of working instances.

      - ##### m_tempUndoFiles

            File[] m_tempUndoFiles

        Keeps track of undo points

      - ##### m_tempUndoIndex

            int m_tempUndoIndex

        The next available slot for an undo point

      - ##### m_UndoBut

            JButton m_UndoBut

        Click to revert back to the last saved point

  - ### Class weka.gui.explorer.PreprocessPanel.PreprocessDefaults

    class PreprocessDefaults extends Defaults implements Serializable

  - ### Class weka.gui.explorer.VisualizePanel

    class VisualizePanel extends AbstractPerspective implements Serializable
    serialVersionUID:
      6084015036853918846L

    - #### Serialized Fields

      - ##### m_Explorer

            Explorer m_Explorer

        the parent frame

      - ##### m_hasInstancesSet

            boolean m_hasInstancesSet

        True if a set of instances has been set on the panel

      - ##### m_matrixPanel

            MatrixPanel m_matrixPanel

  - ### Class weka.gui.explorer.VisualizePanel.ScatterDefaults

    class ScatterDefaults extends Defaults implements Serializable
    serialVersionUID:
      -6890761195767034507L

- ## Package weka.gui.filters

  - ### Class weka.gui.filters.AddUserFieldsCustomizer

    class AddUserFieldsCustomizer extends JPanel implements Serializable
    serialVersionUID:
      -3823417827142174931L

    - #### Serialized Fields

      - ##### m_dateFormatField

            EnvironmentField m_dateFormatField

      - ##### m_deleteBut

            JButton m_deleteBut

      - ##### m_dontShowButs

            boolean m_dontShowButs

      - ##### m_downBut

            JButton m_downBut

      - ##### m_env

            Environment m_env

      - ##### m_filter

            AddUserFields m_filter

        THe filter being customized

      - ##### m_list

            JList m_list

      - ##### m_listModel

            DefaultListModel m_listModel

      - ##### m_modifyL

            BeanCustomizer.ModifyListener m_modifyL

      - ##### m_nameField

            EnvironmentField m_nameField

      - ##### m_newBut

            JButton m_newBut

      - ##### m_typeField

            JComboBox m_typeField

      - ##### m_upBut

            JButton m_upBut

      - ##### m_valueField

            EnvironmentField m_valueField

- ## Package weka.gui.graphvisualizer

  - ### Exception weka.gui.graphvisualizer.BIFFormatException

    class BIFFormatException extends Exception implements Serializable
    serialVersionUID:
      -4102518086411708140L

  - ### Class weka.gui.graphvisualizer.GraphVisualizer

    class GraphVisualizer extends JPanel implements Serializable
    serialVersionUID:
      -2038911085935515624L

    - #### Serialized Fields

      - ##### fm

            FontMetrics fm

      - ##### graphID

            String graphID

        String containing graph's name

      - ##### ICONPATH

            String ICONPATH

        path for icons

      - ##### jBtLayout

            JButton jBtLayout

        Button for laying out the graph again, necessary after changing node's size or some other property of the layout engine

      - ##### jTfNodeHeight

            JTextField jTfNodeHeight

        TextField for nodes height

      - ##### jTfNodeWidth

            JTextField jTfNodeWidth

        TextField for node's width

      - ##### m_edges

            ArrayList<GraphEdge> m_edges

        Vector containing edges

      - ##### m_gp

            weka.gui.graphvisualizer.GraphVisualizer.GraphPanel m_gp

        Panel actually displaying the graph

      - ##### m_jBtSave

            JButton m_jBtSave

        Save button to save the current graph in DOT or XMLBIF format. The graph should be layed out again to get the original form if reloaded from command line, as the formats do not allow saving specific information for a properly layed out graph.

      - ##### m_js

            JScrollPane m_js

        this contains the m_gp GraphPanel

      - ##### m_le

            LayoutEngine m_le

        The current LayoutEngine

      - ##### m_nodes

            ArrayList<GraphNode> m_nodes

        Vector containing nodes

      - ##### maxStringWidth

            int maxStringWidth

        used for setting appropriate node size

      - ##### nodeHeight

            int nodeHeight

      - ##### nodeWidth

            int nodeWidth

      - ##### paddedNodeWidth

            int paddedNodeWidth

      - ##### scale

            double scale

      - ##### zoomPercents

            int[] zoomPercents

        used when using zoomIn and zoomOut buttons

  - ### Class weka.gui.graphvisualizer.LayoutCompleteEvent

    class LayoutCompleteEvent extends EventObject implements Serializable
    serialVersionUID:
      6172467234026258427L

- ## Package weka.gui.hierarchyvisualizer

  - ### Class weka.gui.hierarchyvisualizer.HierarchyVisualizer

    class HierarchyVisualizer extends PrintablePanel implements Serializable
    serialVersionUID:
      1L

    - #### Serialized Fields

      - ##### m_fHeight

            double m_fHeight

      - ##### m_fScaleX

            double m_fScaleX

      - ##### m_fScaleY

            double m_fScaleY

      - ##### m_fTmpLength

            double m_fTmpLength

      - ##### m_nLeafs

            int m_nLeafs

      - ##### m_sNewick

            String m_sNewick

      - ##### m_tree

            weka.gui.hierarchyvisualizer.HierarchyVisualizer.Node m_tree

- ## Package weka.gui.knowledgeflow

  - ### Class weka.gui.knowledgeflow.AttributeSummaryPerspective

    class AttributeSummaryPerspective extends AbstractPerspective implements Serializable
    serialVersionUID:
      6697308901346612850L

    - #### Serialized Fields

      - ##### m_coloringIndex

            int m_coloringIndex

        Index on which to color the plots

      - ##### m_visualizeDataSet

            Instances m_visualizeDataSet

        The dataset being visualized

  - ### Class weka.gui.knowledgeflow.AttributeSummaryPerspective.AttDefaults

    class AttDefaults extends Defaults implements Serializable
    serialVersionUID:
      -32801466385262321L

  - ### Class weka.gui.knowledgeflow.BaseInteractiveViewer

    class BaseInteractiveViewer extends JPanel implements Serializable
    serialVersionUID:
      -1191494001428785466L

    - #### Serialized Fields

      - ##### m_buttonHolder

            JPanel m_buttonHolder

        Holds buttons displayed at the bottom of the window

      - ##### m_closeBut

            JButton m_closeBut

        The close button, for closing the viewer

      - ##### m_mainPerspective

            MainKFPerspective m_mainPerspective

        The main Knowledge Flow perspective

      - ##### m_parent

            Window m_parent

        The parent window

      - ##### m_step

            Step m_step

        Holds the step that this interactive viewer relates to

  - ### Class weka.gui.knowledgeflow.DesignPanel

    class DesignPanel extends JPanel implements Serializable
    serialVersionUID:
      3324733191950871564L

  - ### Class weka.gui.knowledgeflow.GOEStepEditorDialog

    class GOEStepEditorDialog extends StepEditorDialog implements Serializable
    serialVersionUID:
      -2500973437145276268L

    - #### Serialized Fields

      - ##### m_editor

            PropertySheetPanel m_editor

        Main editor for the step - used for editing properties of the step or properties of a wrapped algorithm (if the step is a subclass of `WekaAlgorithmWrapper`.

      - ##### m_editorHolder

            JPanel m_editorHolder

        The main holder panel

      - ##### m_manager

            StepManagerImpl m_manager

        The `StepManager` for the step being edited

      - ##### m_primaryEditorHolder

            JPanel m_primaryEditorHolder

        The panel that contains the main editor

      - ##### m_secondaryEditor

            PropertySheetPanel m_secondaryEditor

        Secondary editor. Used for additional properties that belong to a Step that extends `WekaAlgorithmWrapper`

      - ##### m_stepOriginal

            Step m_stepOriginal

        Holds a copy of the step (for restoring after cancel)

  - ### Class weka.gui.knowledgeflow.InvisibleNode

    class InvisibleNode extends DefaultMutableTreeNode implements Serializable
    serialVersionUID:
      -9064396835384819887L

    - #### Serialized Fields

      - ##### m_isVisible

            boolean m_isVisible

        True if the node is visible

  - ### Class weka.gui.knowledgeflow.InvisibleTreeModel

    class InvisibleTreeModel extends DefaultTreeModel implements Serializable
    serialVersionUID:
      6940101211275068260L

    - #### Serialized Fields

      - ##### m_filterIsActive

            boolean m_filterIsActive

        True if the visibility filter is active

  - ### Class weka.gui.knowledgeflow.KnowledgeFlowApp

    class KnowledgeFlowApp extends AbstractGUIApplication implements Serializable
    serialVersionUID:
      -1460599392623083983L

    - #### Serialized Fields

      - ##### m_kfProperties

            Settings m_kfProperties

        Settings for the Knowledge Flow

      - ##### m_mainPerspective

            MainKFPerspective m_mainPerspective

        Main perspective of the Knowledge Flow

  - ### Class weka.gui.knowledgeflow.KnowledgeFlowApp.KnowledgeFlowGeneralDefaults

    class KnowledgeFlowGeneralDefaults extends Defaults implements Serializable
    serialVersionUID:
      6957165806947500265L

  - ### Class weka.gui.knowledgeflow.LayoutPanel

    class LayoutPanel extends PrintablePanel implements Serializable
    serialVersionUID:
      4988098224376217099L

    - #### Serialized Fields

      - ##### m_currentX

            int m_currentX

      - ##### m_currentY

            int m_currentY

      - ##### m_gridSpacing

            int m_gridSpacing

        Grid spacing

      - ##### m_oldX

            int m_oldX

      - ##### m_oldY

            int m_oldY

      - ##### m_perspectiveDataLoadThread

            Thread m_perspectiveDataLoadThread

        Thread for loading data for perspectives

      - ##### m_visLayout

            VisibleLayout m_visLayout

        The flow contained in this LayoutPanel as a visible (graphical) flow

  - ### Class weka.gui.knowledgeflow.MainKFPerspective

    class MainKFPerspective extends AbstractPerspective implements Serializable
    serialVersionUID:
      3986047323839299447L

    - #### Serialized Fields

      - ##### m_allowMultipleTabs

            boolean m_allowMultipleTabs

        Whether to allow multiple tabs

      - ##### m_FileChooser

            WekaFileChooser m_FileChooser

        The file chooser for loading layout files

      - ##### m_flowGraphs

            List<VisibleLayout> m_flowGraphs

        List of layouts - one for each tab

      - ##### m_flowTabs

            JTabbedPane m_flowTabs

        Holds the tabs of the perspective

      - ##### m_mainToolBar

            MainKFPerspectiveToolBar m_mainToolBar

        Main toolbar

      - ##### m_palleteSelectedStep

            StepManagerImpl m_palleteSelectedStep

        The current step selected from the design pallete

      - ##### m_pasteBuffer

            String m_pasteBuffer

        The paste buffer

      - ##### m_saveFileChooser

            WekaFileChooser m_saveFileChooser

        The file chooser for saving layout files (only supports saving as json .kf files

      - ##### m_stepTree

            StepTree m_stepTree

        The jtree holding steps

      - ##### m_templateManager

            TemplateManager m_templateManager

        Manages template flows

      - ##### m_untitledCount

            int m_untitledCount

        Count for new "untitled" tabs

  - ### Class weka.gui.knowledgeflow.MainKFPerspectiveToolBar

    class MainKFPerspectiveToolBar extends JPanel implements Serializable
    serialVersionUID:
      -157986423490835642L

    - #### Serialized Fields

      - ##### m_mainPerspective

            MainKFPerspective m_mainPerspective

        Reference to the main knowledge flow perspective

      - ##### m_menuItemMap

            Map<String,JMenuItem> m_menuItemMap

        holds a map of menu items (for widgets that have corresponding menu items)

      - ##### m_menuMap

            Map<String,JMenu> m_menuMap

        Holds a map of top level menus

      - ##### m_showMenus

            boolean m_showMenus

        True if menu items corresponding to the toolbar widgets should be shown

      - ##### m_widgetMap

            Map<String,JComponent> m_widgetMap

        holds a map of widgets, keyed by widget name

  - ### Class weka.gui.knowledgeflow.NoteVisual

    class NoteVisual extends StepVisual implements Serializable
    serialVersionUID:
      -3291021235652124916L

    - #### Serialized Fields

      - ##### m_fontSizeAdjust

            int m_fontSizeAdjust

        Adjustment for the font size

      - ##### m_label

            JLabel m_label

        The label that displays the note text

  - ### Class weka.gui.knowledgeflow.ScatterPlotMatrixPerspective

    class ScatterPlotMatrixPerspective extends AbstractPerspective implements Serializable
    serialVersionUID:
      5661598509822826837L

    - #### Serialized Fields

      - ##### m_matrixPanel

            MatrixPanel m_matrixPanel

        The actual matrix panel

      - ##### m_visualizeDataSet

            Instances m_visualizeDataSet

        The dataset being visualized

  - ### Class weka.gui.knowledgeflow.ShadowBorder

    class ShadowBorder extends AbstractBorder implements Serializable
    serialVersionUID:
      -2117842133475125463L

    - #### Serialized Fields

      - ##### m_color

            Color m_color

        the color of the drop shadow

      - ##### m_width

            int m_width

        The width in pixels of the drop shadow

  - ### Class weka.gui.knowledgeflow.SQLViewerPerspective

    class SQLViewerPerspective extends AbstractPerspective implements Serializable
    serialVersionUID:
      -4771310190331379801L

    - #### Serialized Fields

      - ##### m_buttonHolder

            JPanel m_buttonHolder

        Panel for holding buttons

      - ##### m_mainKFPerspective

            MainKFPerspective m_mainKFPerspective

        Reference to tne main knowledge flow perspective

      - ##### m_newFlowBut

            JButton m_newFlowBut

        Button for creating a new flow layout with a configured DBLoader step

      - ##### m_viewer

            SqlViewer m_viewer

        The wrapped SQLViewer

  - ### Class weka.gui.knowledgeflow.SQLViewerPerspective.SQLDefaults

    class SQLDefaults extends Defaults implements Serializable
    serialVersionUID:
      5907476861935295960L

  - ### Class weka.gui.knowledgeflow.StepEditorDialog

    class StepEditorDialog extends JPanel implements Serializable
    serialVersionUID:
      -4860182109190301676L

    - #### Serialized Fields

      - ##### m_buttonHolder

            JPanel m_buttonHolder

        Holder for buttons

      - ##### m_cancelBut

            JButton m_cancelBut

        Cancel button

      - ##### m_closingListener

            StepEditorDialog.ClosingListener m_closingListener

        Listener to be informed when the window closes

      - ##### m_commandHandler

            KFGraphicalEnvironmentCommandHandler m_commandHandler

        The handler for graphical commands

      - ##### m_env

            Environment m_env

        Environment variables

      - ##### m_helpBut

            JButton m_helpBut

        About button

      - ##### m_helpText

            StringBuilder m_helpText

        Buffer to hold the help text

      - ##### m_isEdited

            boolean m_isEdited

        True if the step's properties have been altered

      - ##### m_mainPerspective

            MainKFPerspective m_mainPerspective

        Reference to the main perspective

      - ##### m_okBut

            JButton m_okBut

        OK button

      - ##### m_parent

            Window m_parent

        Parent window

      - ##### m_settingsBut

            JButton m_settingsBut

        Settings button

      - ##### m_stepToEdit

            Step m_stepToEdit

        The step to edit

  - ### Class weka.gui.knowledgeflow.StepTree

    class StepTree extends JTree implements Serializable
    serialVersionUID:
      3646119269455293741L

    - #### Serialized Fields

      - ##### m_mainPerspective

            MainKFPerspective m_mainPerspective

        Reference to the main knowledge flow perspective

      - ##### m_nodeTextIndex

            Map<String,DefaultMutableTreeNode> m_nodeTextIndex

        Lookup for searching text of global info/tip texts

  - ### Class weka.gui.knowledgeflow.StepTree.StepIconRenderer

    class StepIconRenderer extends DefaultTreeCellRenderer implements Serializable
    serialVersionUID:
      -4488876734500244945L

  - ### Class weka.gui.knowledgeflow.StepTreeLeafDetails

    class StepTreeLeafDetails extends Object implements Serializable
    serialVersionUID:
      6347861816716877761L

    - #### Serialized Fields

      - ##### m_leafLabel

            String m_leafLabel

        the label (usually derived from the qualified name or wrapped algorithm) for the leaf

      - ##### m_showTipText

            boolean m_showTipText

        If a tool tip text is set, whether to show it or not

      - ##### m_stepClazz

            Class m_stepClazz

        Class of the step stored at this leaf

      - ##### m_toolTipText

            String m_toolTipText

        tool tip text to display

      - ##### m_wrappedWekaAlgoName

            String m_wrappedWekaAlgoName

        The name of the algorithm wrapped by a WekaAlgorithmWrapper step

  - ### Class weka.gui.knowledgeflow.StepVisual

    class StepVisual extends JPanel implements Serializable
    serialVersionUID:
      4156046438296843760L

    - #### Serialized Fields

      - ##### m_connectorColor

            Color m_connectorColor

        Current connector dot colour

      - ##### m_displayConnectors

            boolean m_displayConnectors

        Whether to display connector dots

      - ##### m_icon

            ImageIcon m_icon

        The icon for the step this visual represents

      - ##### m_stepManager

            StepManagerImpl m_stepManager

        The step manager for the step this visual represents

      - ##### m_x

            int m_x

        The x coordinate of the step on the graphical layout

      - ##### m_y

            int m_y

        The y coordinate of the step on the graphical layout

  - ### Class weka.gui.knowledgeflow.VisibleLayout

    class VisibleLayout extends JPanel implements Serializable
    serialVersionUID:
      -3644458365810712479L

    - #### Serialized Fields

      - ##### m_editConnection

            String m_editConnection

        The name of the user-selected connection if the user has initiated a connection from a source step (stored in m_editStep)

      - ##### m_editStep

            StepVisual m_editStep

        Reference to the step being edited (if any)

      - ##### m_env

            Environment m_env

        Environment variables to use

      - ##### m_filePath

            File m_filePath

        Current path on disk for this flow

      - ##### m_flow

            Flow m_flow

      - ##### m_flowExecutor

            FlowExecutor m_flowExecutor

        The flow executor used to execute the flow

      - ##### m_hasBeenEdited

            boolean m_hasBeenEdited

        True if the flow has been edited, but not yet saved

      - ##### m_isExecuting

            boolean m_isExecuting

        True if this flow is executing

      - ##### m_layout

            LayoutPanel m_layout

        The panel used to render the flow

      - ##### m_logPanel

            weka.gui.knowledgeflow.VisibleLayout.KFLogPanel m_logPanel

        The log panel to use for this layout

      - ##### m_mainPerspective

            MainKFPerspective m_mainPerspective

        A reference to the main perspective

      - ##### m_renderGraph

            List<StepVisual> m_renderGraph

        The steps to be rendered on this layout

      - ##### m_selectedSteps

            List<StepVisual> m_selectedSteps

        Keeps track of any highlighted steps on the canvas

      - ##### m_undoBuffer

            Stack<File> m_undoBuffer

        Keeps track of the undo buffer for this flow

      - ##### m_userOpp

            weka.gui.knowledgeflow.VisibleLayout.LayoutOperation m_userOpp

        The current layout operation

      - ##### m_zoomSetting

            int m_zoomSetting

        Current zoom setting for this layout

  - ### Class weka.gui.knowledgeflow.VisibleLayout.KFLogPanel

    class KFLogPanel extends LogPanel implements Serializable
    serialVersionUID:
      -2224509243343105276L

- ## Package weka.gui.knowledgeflow.steps

  - ### Class weka.gui.knowledgeflow.steps.ASEvaluatorStepEditorDialog

    class ASEvaluatorStepEditorDialog extends GOEStepEditorDialog implements Serializable
    serialVersionUID:
      -166234654984288982L

    - #### Serialized Fields

      - ##### m_treatXValFoldsSeparately

            JCheckBox m_treatXValFoldsSeparately

        Check box for selecting whether to treat x-val folds separately or not

  - ### Class weka.gui.knowledgeflow.steps.AttributeSummarizerInteractiveView

    class AttributeSummarizerInteractiveView extends BaseInteractiveViewer implements Serializable
    serialVersionUID:
      -8080574605631027263L

    - #### Serialized Fields

      - ##### m_clearButton

            JButton m_clearButton

        Button for clearing all results

      - ##### m_currentInstances

            Instances m_currentInstances

        The instances being visualized

      - ##### m_history

            ResultHistoryPanel m_history

        Holds results

      - ##### m_splitPane

            JSplitPane m_splitPane

        Split pane to separate result list from visualization

      - ##### m_summarizer

            AttributeSummaryPerspective m_summarizer

        Holds the actual visualization

  - ### Class weka.gui.knowledgeflow.steps.AttributeSummarizerStepEditorDialog

    class AttributeSummarizerStepEditorDialog extends ModelPerformanceChartStepEditorDialog implements Serializable
    serialVersionUID:
      -4504946065343184549L

  - ### Class weka.gui.knowledgeflow.steps.BlockStepEditorDialog

    class BlockStepEditorDialog extends StepEditorDialog implements Serializable
    serialVersionUID:
      1183316309880876170L

    - #### Serialized Fields

      - ##### m_stepToBlockBox

            JComboBox<String> m_stepToBlockBox

        The combo box for choosing the step to block on

  - ### Class weka.gui.knowledgeflow.steps.BoundaryPlotterInteractiveView

    class BoundaryPlotterInteractiveView extends BaseInteractiveViewer implements Serializable
    serialVersionUID:
      5567187861739468636L

    - #### Serialized Fields

      - ##### m_clearButton

            JButton m_clearButton

      - ##### m_history

            ResultHistoryPanel m_history

        Holds a list of plots

      - ##### m_plotter

            weka.gui.knowledgeflow.steps.ImageViewerInteractiveView.ImageDisplayer m_plotter

        Panel for displaying the image

  - ### Class weka.gui.knowledgeflow.steps.BoundaryPlotterStepEditorDialog

    class BoundaryPlotterStepEditorDialog extends GOEStepEditorDialog implements Serializable
    serialVersionUID:
      4351742205211273840L

    - #### Serialized Fields

      - ##### m_xCombo

            JComboBox<String> m_xCombo

        Combo box for selecting the x attribute to plot when there is an incoming instances structure at design time

      - ##### m_xEnviro

            EnvironmentField m_xEnviro

        Environment field for specifying the x attribute when there isn't incoming instances structure at design time

      - ##### m_yCombo

            JComboBox<String> m_yCombo

        Combo box for selecting the y attribute to plot when there is an incoming instances structure at design time

      - ##### m_yEnviro

            EnvironmentField m_yEnviro

        Environment field for specifying the y attribute when there isn't incoming instances structure at design time

  - ### Class weka.gui.knowledgeflow.steps.ClassAssignerStepEditorDialog

    class ClassAssignerStepEditorDialog extends GOEStepEditorDialog implements Serializable
    serialVersionUID:
      3105898651212196539L

    - #### Serialized Fields

      - ##### m_classCombo

            JComboBox<String> m_classCombo

        Combo box for selecting the class attribute

  - ### Class weka.gui.knowledgeflow.steps.ClassifierPerformanceEvaluatorStepEditorDialog

    class ClassifierPerformanceEvaluatorStepEditorDialog extends GOEStepEditorDialog implements Serializable
    serialVersionUID:
      -4459460141076392499L

    - #### Serialized Fields

      - ##### m_CostMatrixEditor

            CostMatrixEditor m_CostMatrixEditor

        The cost matrix editor for evaluation costs.

      - ##### m_evaluationMetrics

            List<String> m_evaluationMetrics

        Holds selected evaluation metrics

      - ##### m_setCostMatrix

            JButton m_setCostMatrix

        Button for popping up cost editor

      - ##### m_SetCostsFrame

            PropertyDialog m_SetCostsFrame

        The frame used to show the cost matrix editing panel.

      - ##### m_showEvalDialog

            JButton m_showEvalDialog

        Button for popping up the evaluation metrics selector dialog

      - ##### m_useCosts

            JCheckBox m_useCosts

        Checkbox for selecting cost-sensitive evaluation

  - ### Class weka.gui.knowledgeflow.steps.ClassValuePickerStepEditorDialog

    class ClassValuePickerStepEditorDialog extends GOEStepEditorDialog implements Serializable
    serialVersionUID:
      7009335918650499183L

    - #### Serialized Fields

      - ##### m_classValueCombo

            JComboBox m_classValueCombo

        For displaying class values

  - ### Class weka.gui.knowledgeflow.steps.CostBenefitAnalysisInteractiveView

    class CostBenefitAnalysisInteractiveView extends BaseInteractiveViewer implements Serializable
    serialVersionUID:
      4624182171551712860L

    - #### Serialized Fields

      - ##### m_cbPanel

            CostBenefitAnalysisPanel m_cbPanel

        The actual cost benefit panel

      - ##### m_clearButton

            JButton m_clearButton

        Button for clearing all results

      - ##### m_history

            ResultHistoryPanel m_history

        Holds result entries

      - ##### m_splitPane

            JSplitPane m_splitPane

        JSplit pane for separating the result list from the visualization

  - ### Class weka.gui.knowledgeflow.steps.DataGridStepEditorDialog

    class DataGridStepEditorDialog extends StepEditorDialog implements Serializable
    serialVersionUID:
      -7314471130292016602L

    - #### Serialized Fields

      - ##### m_attNameField

            EnvironmentField m_attNameField

        Field for editing an attribute name

      - ##### m_attTypeField

            JComboBox<String> m_attTypeField

        Combo box for selecting the type of the attribute

      - ##### m_deleteBut

            JButton m_deleteBut

        Button for deleting an attribute def

      - ##### m_downBut

            JButton m_downBut

        Button for moving an attribute down in the list

      - ##### m_list

            JList<weka.gui.knowledgeflow.steps.DataGridStepEditorDialog.AttDef> m_list

        Holds the list of attribute defs

      - ##### m_listModel

            DefaultListModel<weka.gui.knowledgeflow.steps.DataGridStepEditorDialog.AttDef> m_listModel

        List model

      - ##### m_newBut

            JButton m_newBut

        Button for adding a new attribute def

      - ##### m_nominalOrDateFormatField

            EnvironmentField m_nominalOrDateFormatField

        Field for editing nominal values/date format string

      - ##### m_stringInstances

            String m_stringInstances

        The instances data from the step as a string

      - ##### m_tabbedPane

            JTabbedPane m_tabbedPane

        Tabbed pane for the two parts of the editor

      - ##### m_upBut

            JButton m_upBut

        Button for moving an attribute up in the list

      - ##### m_viewerPanel

            weka.gui.knowledgeflow.steps.DataGridStepEditorDialog.ArffViewerPanel m_viewerPanel

        Panel for viewing/editing the instances data

  - ### Class weka.gui.knowledgeflow.steps.DataGridStepEditorDialog.ArffViewerPanel

    class ArffViewerPanel extends JPanel implements Serializable
    serialVersionUID:
      2965315087365186710L

    - #### Serialized Fields

      - ##### m_addInstanceButton

            JButton m_addInstanceButton

        Click to add a new instance to the end of the dataset

      - ##### m_ArffPanel

            ArffPanel m_ArffPanel

        the panel to display the Instances-object

      - ##### m_UndoButton

            JButton m_UndoButton

        Click to undo the last action

  - ### Class weka.gui.knowledgeflow.steps.DataVisualizerInteractiveView

    class DataVisualizerInteractiveView extends BaseInteractiveViewer implements Serializable
    serialVersionUID:
      5345799787154266282L

    - #### Serialized Fields

      - ##### m_clearButton

            JButton m_clearButton

        Button for clearing all results

      - ##### m_currentPlot

            PlotData2D m_currentPlot

        Curent plot data

      - ##### m_history

            ResultHistoryPanel m_history

        Holds results

      - ##### m_splitPane

            JSplitPane m_splitPane

        Split pane for separating result list from visualization

      - ##### m_visPanel

            VisualizePanel m_visPanel

        The actual visualization

  - ### Class weka.gui.knowledgeflow.steps.DataVisualizerStepEditorDialog

    class DataVisualizerStepEditorDialog extends ModelPerformanceChartStepEditorDialog implements Serializable
    serialVersionUID:
      -6032558757326543902L

  - ### Class weka.gui.knowledgeflow.steps.ExecuteProcessStepEditorDialog

    class ExecuteProcessStepEditorDialog extends StepEditorDialog implements Serializable
    serialVersionUID:
      -7740004961609720209L

    - #### Serialized Fields

      - ##### m_dynamicPanel

            weka.gui.knowledgeflow.steps.ExecuteProcessStepEditorDialog.DynamicProcessPanel m_dynamicPanel

        Panel for dynamic commands

      - ##### m_raiseExceptonOnCommandFailure

            JCheckBox m_raiseExceptonOnCommandFailure

        Checkbox to indicate whether complete command failure (vs just returning a non-zero status) should generate an exception

      - ##### m_staticPanel

            weka.gui.knowledgeflow.steps.ExecuteProcessStepEditorDialog.StaticProcessPanel m_staticPanel

        Panel for static commands

      - ##### m_useDynamicCheck

            JCheckBox m_useDynamicCheck

        Checkbox to indicate whether dynamic commands are to be executed

  - ### Class weka.gui.knowledgeflow.steps.ExecuteProcessStepEditorDialog.DynamicProcessPanel

    class DynamicProcessPanel extends JPanel implements Serializable
    serialVersionUID:
      6440523583792476595L

    - #### Serialized Fields

      - ##### m_argsField

            JComboBox<String> m_argsField

      - ##### m_cmdField

            JComboBox<String> m_cmdField

      - ##### m_workingDirField

            JComboBox<String> m_workingDirField

  - ### Class weka.gui.knowledgeflow.steps.ExecuteProcessStepEditorDialog.StaticProcessPanel

    class StaticProcessPanel extends JPanel implements Serializable
    serialVersionUID:
      -4215730214067279661L

    - #### Serialized Fields

      - ##### m_argsText

            JTextField m_argsText

      - ##### m_cmdText

            JTextField m_cmdText

      - ##### m_workingDirField

            FileEnvironmentField m_workingDirField

  - ### Class weka.gui.knowledgeflow.steps.FlowByExpressionStepEditorDialog

    class FlowByExpressionStepEditorDialog extends StepEditorDialog implements Serializable
    serialVersionUID:
      1545740909421963983L

    - #### Serialized Fields

      - ##### m_addBracketNode

            JButton m_addBracketNode

        Button for adding a new brackets node to the expression tree

      - ##### m_addExpressionNode

            JButton m_addExpressionNode

        Button for adding a new expression node to the expression tree

      - ##### m_andOr

            JButton m_andOr

        Button for and/or

      - ##### m_deleteNode

            JButton m_deleteNode

        Button for deleting a node from the expression tree

      - ##### m_expressionLab

            JLabel m_expressionLab

        Label for displaying the current expression

      - ##### m_expressionTree

            JTree m_expressionTree

        Holds the tree view of the expression

      - ##### m_falseData

            JComboBox<String> m_falseData

        Combo box for choosing the downstream step that instances failing to match the expression should go to

      - ##### m_lhsField

            JComboBox m_lhsField

        Combo box for the LHS of the expression being entered

      - ##### m_operatorCombo

            JComboBox<String> m_operatorCombo

        Combo box for choosing the operator

      - ##### m_rhsField

            JComboBox m_rhsField

        Combo box for the RHS of the expression being entered

      - ##### m_rhsIsAttribute

            JCheckBox m_rhsIsAttribute

        Check box for indicating that the RHS is the name of an attribute

      - ##### m_toggleNegation

            JButton m_toggleNegation

        Button for toggling negation

      - ##### m_treeRoot

            DefaultMutableTreeNode m_treeRoot

        Root of the tree

      - ##### m_trueData

            JComboBox<String> m_trueData

        Combo box for choosing the downstream step that instances matching the expression should go to

  - ### Class weka.gui.knowledgeflow.steps.GraphViewerInteractiveView

    class GraphViewerInteractiveView extends BaseInteractiveViewer implements Serializable
    serialVersionUID:
      2109423349272114409L

    - #### Serialized Fields

      - ##### m_clearButton

            JButton m_clearButton

        Button for clearing the results

      - ##### m_graphVisualizer

            GraphVisualizer m_graphVisualizer

        Visualization component for graphs

      - ##### m_history

            ResultHistoryPanel m_history

        Holds a list of results

      - ##### m_holderPanel

            JPanel m_holderPanel

        Holder panel for layout purposes

      - ##### m_splitPane

            JSplitPane m_splitPane

        Split pane for separating the results list from the visualization

      - ##### m_treeVisualizer

            TreeVisualizer m_treeVisualizer

        Visualization component for trees

  - ### Class weka.gui.knowledgeflow.steps.ImageViewerInteractiveView

    class ImageViewerInteractiveView extends BaseInteractiveViewer implements Serializable
    serialVersionUID:
      -6652203133445653870L

    - #### Serialized Fields

      - ##### m_clearButton

            JButton m_clearButton

        Button for clearing the results

      - ##### m_history

            ResultHistoryPanel m_history

        A panel for holding a list of results

      - ##### m_plotter

            weka.gui.knowledgeflow.steps.ImageViewerInteractiveView.ImageDisplayer m_plotter

        Panel for displaying the image

  - ### Class weka.gui.knowledgeflow.steps.ImageViewerInteractiveView.ImageDisplayer

    class ImageDisplayer extends JPanel implements Serializable
    serialVersionUID:
      4161957589912537357L

    - #### Serialized Fields

      - ##### m_image

            BufferedImage m_image

        The image to display

      - ##### m_imageZoom

            int m_imageZoom

  - ### Class weka.gui.knowledgeflow.steps.ImageViewerInteractiveView.MainPanel

    class MainPanel extends JPanel implements Serializable
    serialVersionUID:
      5648976848887609072L

  - ### Class weka.gui.knowledgeflow.steps.JobStepEditorDialog

    class JobStepEditorDialog extends GOEStepEditorDialog implements Serializable
    serialVersionUID:
      -4921559717867446684L

    - #### Serialized Fields

      - ##### m_editSubFlow

            JButton m_editSubFlow

        Button for loading the sub-flow in a new tab

  - ### Class weka.gui.knowledgeflow.steps.JoinStepEditorDialog

    class JoinStepEditorDialog extends StepEditorDialog implements Serializable
    serialVersionUID:
      -2648770811063889717L

    - #### Serialized Fields

      - ##### m_addOneBut

            JButton m_addOneBut

        Add button for the first instance stream

      - ##### m_addTwoBut

            JButton m_addTwoBut

        Add button for the second instance stream

      - ##### m_deleteOneBut

            JButton m_deleteOneBut

        Delete button for the first instance stream

      - ##### m_deleteTwoBut

            JButton m_deleteTwoBut

        Delete button for the second instance stream

      - ##### m_downOneBut

            JButton m_downOneBut

        Move down button for the first instance stream

      - ##### m_downTwoBut

            JButton m_downTwoBut

        Move down button for the second instance stream

      - ##### m_firstKeyFields

            JComboBox m_firstKeyFields

        Combo box for selecting a key field to add from the first instance stream

      - ##### m_firstList

            JList m_firstList

        List of selected key fields for the first instance stream

      - ##### m_firstListModel

            DefaultListModel<String> m_firstListModel

      - ##### m_secondKeyFields

            JComboBox m_secondKeyFields

        Combo box for selecting a the key field to add from the second instance stream

      - ##### m_secondList

            JList m_secondList

        List of selected key fields for the second instance stream

      - ##### m_secondListModel

            DefaultListModel<String> m_secondListModel

      - ##### m_upOneBut

            JButton m_upOneBut

        Move up button for the first instance stream

      - ##### m_upTwoBut

            JButton m_upTwoBut

        Move up button for the second instance stream

  - ### Class weka.gui.knowledgeflow.steps.LoaderStepEditorDialog

    class LoaderStepEditorDialog extends GOEStepEditorDialog implements Serializable
    serialVersionUID:
      -6501371943783384741L

    - #### Serialized Fields

      - ##### m_fileLoader

            FileEnvironmentField m_fileLoader

        Widget for specifying/choosing a file for file-based loaders

  - ### Class weka.gui.knowledgeflow.steps.ModelPerformanceChartInteractiveView

    class ModelPerformanceChartInteractiveView extends BaseInteractiveViewer implements Serializable
    serialVersionUID:
      8818417648798221980L

    - #### Serialized Fields

      - ##### m_clearButton

            JButton m_clearButton

        Button for clearing results

      - ##### m_visPanel

            VisualizePanel m_visPanel

        The actual visualization

  - ### Class weka.gui.knowledgeflow.steps.ModelPerformanceChartStepEditorDialog

    class ModelPerformanceChartStepEditorDialog extends GOEStepEditorDialog implements Serializable
    serialVersionUID:
      -3031265139980301695L

    - #### Serialized Fields

      - ##### m_currentRendererName

            String m_currentRendererName

        Currently selected renderer name

      - ##### m_currentRendererOptions

            String m_currentRendererOptions

        Current renderer options

      - ##### m_offscreenSelector

            JComboBox<String> m_offscreenSelector

        For selecting the renderer to use

      - ##### m_rendererOptions

            EnvironmentField m_rendererOptions

        For editing the renderer options

  - ### Class weka.gui.knowledgeflow.steps.NoteEditorDialog

    class NoteEditorDialog extends StepEditorDialog implements Serializable
    serialVersionUID:
      2358735294813135692L

    - #### Serialized Fields

      - ##### m_textArea

            JTextArea m_textArea

        Text area of the note

  - ### Class weka.gui.knowledgeflow.steps.SaverStepEditorDialog

    class SaverStepEditorDialog extends GOEStepEditorDialog implements Serializable
    serialVersionUID:
      -8353826767500440827L

    - #### Serialized Fields

      - ##### m_directory

            FileEnvironmentField m_directory

        Field for specifying the directory to save into

      - ##### m_dirLab

            JLabel m_dirLab

        Label for the directory field

      - ##### m_prefixOrFile

            EnvironmentField m_prefixOrFile

        Field for specifying either the file prefix to use or the actual filename itself

      - ##### m_prefLab

            JLabel m_prefLab

        Label for the file/prefix field

  - ### Class weka.gui.knowledgeflow.steps.ScatterPlotMatrixInteractiveView

    class ScatterPlotMatrixInteractiveView extends BaseInteractiveViewer implements Serializable
    serialVersionUID:
      275603100387301133L

    - #### Serialized Fields

      - ##### m_clearButton

            JButton m_clearButton

        Button for clearing the results list

      - ##### m_history

            ResultHistoryPanel m_history

        Holds a list of results

      - ##### m_matrixPanel

            MatrixPanel m_matrixPanel

        The actual visualization

      - ##### m_splitPane

            JSplitPane m_splitPane

        Split pane for separating the result list and visualization

  - ### Class weka.gui.knowledgeflow.steps.SendToPerspectiveStepEditorDialog

    class SendToPerspectiveStepEditorDialog extends GOEStepEditorDialog implements Serializable
    serialVersionUID:
      -8282588308511754826L

    - #### Serialized Fields

      - ##### m_perspectivesCombo

            JComboBox<String> m_perspectivesCombo

        Combo box for selecting the perspective to send to

  - ### Class weka.gui.knowledgeflow.steps.SetVariablesStepEditorDialog

    class SetVariablesStepEditorDialog extends StepEditorDialog implements Serializable
    serialVersionUID:
      5747505623497131129L

    - #### Serialized Fields

      - ##### m_dvp

            weka.gui.knowledgeflow.steps.SetVariablesStepEditorDialog.DynamicVariablesPanel m_dvp

      - ##### m_vp

            weka.gui.knowledgeflow.steps.SetVariablesStepEditorDialog.VariablesPanel m_vp

        panel for editing variables

  - ### Class weka.gui.knowledgeflow.steps.SetVariablesStepEditorDialog.DynamicVariablesPanel

    class DynamicVariablesPanel extends JPanel implements Serializable
    serialVersionUID:
      -280047347103350039L

    - #### Serialized Fields

      - ##### m_table

            InteractiveTablePanel m_table

  - ### Class weka.gui.knowledgeflow.steps.SetVariablesStepEditorDialog.VariablesPanel

    class VariablesPanel extends JPanel implements Serializable
    serialVersionUID:
      5188290550108775006L

    - #### Serialized Fields

      - ##### m_table

            InteractiveTablePanel m_table

  - ### Class weka.gui.knowledgeflow.steps.SorterStepEditorDialog

    class SorterStepEditorDialog extends GOEStepEditorDialog implements Serializable
    serialVersionUID:
      -1258170590422372948L

    - #### Serialized Fields

      - ##### m_attCombo

            JComboBox<String> m_attCombo

        Combo box for selecting attribute to sort on

      - ##### m_deleteBut

            JButton m_deleteBut

        Button for deleting a selected rule

      - ##### m_descending

            JComboBox<String> m_descending

        Combo box for choosing to sort descending or not

      - ##### m_downBut

            JButton m_downBut

        Button for moving a rule down in the list

      - ##### m_list

            JList<Sorter.SortRule> m_list

        Holds the individual sorting criteria

      - ##### m_listModel

            DefaultListModel<Sorter.SortRule> m_listModel

        List model for sort rules

      - ##### m_newBut

            JButton m_newBut

        Button for creating a new rule

      - ##### m_upBut

            JButton m_upBut

        Button for moving a rule up in the list

  - ### Class weka.gui.knowledgeflow.steps.StorePropertiesInEnvironmentStepEditorDialog

    class StorePropertiesInEnvironmentStepEditorDialog extends StepEditorDialog implements Serializable
    serialVersionUID:
      3797813883697010599L

    - #### Serialized Fields

      - ##### m_dpp

            weka.gui.knowledgeflow.steps.StorePropertiesInEnvironmentStepEditorDialog.DynamicPropertiesPanel m_dpp

  - ### Class weka.gui.knowledgeflow.steps.StorePropertiesInEnvironmentStepEditorDialog.DynamicPropertiesPanel

    class DynamicPropertiesPanel extends JPanel implements Serializable
    serialVersionUID:
      5864117781960584665L

    - #### Serialized Fields

      - ##### m_table

            InteractiveTablePanel m_table

  - ### Class weka.gui.knowledgeflow.steps.StripChartInteractiveView

    class StripChartInteractiveView extends BaseInteractiveViewer implements Serializable
    serialVersionUID:
      7697752421621805402L

    - #### Serialized Fields

      - ##### m_BackgroundColor

            Color m_BackgroundColor

        the background color.

      - ##### m_colorList

            Color[] m_colorList

        default colours for colouring lines

      - ##### m_iheight

            int m_iheight

        Width and height of the off screen image.

      - ##### m_iwidth

            int m_iwidth

      - ##### m_labelFont

            Font m_labelFont

        Font to use on the plot

      - ##### m_labelMetrics

            FontMetrics m_labelMetrics

        Font metrics for string placement calculations

      - ##### m_legendPanel

            weka.gui.knowledgeflow.steps.StripChartInteractiveView.LegendPanel m_legendPanel

        Holds the legend

      - ##### m_LegendPanelBorderColor

            Color m_LegendPanelBorderColor

        the color of the legend panel's border.

      - ##### m_legendText

            List<String> m_legendText

        Holds the legend entries

      - ##### m_max

            double m_max

        Max value for the y axis.

      - ##### m_min

            double m_min

        Min value for the y axis.

      - ##### m_oldMax

            double m_oldMax

      - ##### m_oldMin

            double m_oldMin

      - ##### m_plotPanel

            weka.gui.knowledgeflow.steps.StripChartInteractiveView.StripPlotter m_plotPanel

      - ##### m_previousY

            double[] m_previousY

        Previous data point

      - ##### m_refreshWidth

            int m_refreshWidth

        Shift the plot by this many pixels every time a point is plotted

      - ##### m_scalePanel

            weka.gui.knowledgeflow.steps.StripChartInteractiveView.ScalePanel m_scalePanel

        the scale.

      - ##### m_xCount

            int m_xCount

        data point count

      - ##### m_yScaleUpdate

            boolean m_yScaleUpdate

        Scale update requested.

  - ### Class weka.gui.knowledgeflow.steps.StripChartInteractiveView.LegendPanel

    class LegendPanel extends JPanel implements Serializable
    serialVersionUID:
      7713986576833797583L

  - ### Class weka.gui.knowledgeflow.steps.StripChartInteractiveView.StripChartInteractiveViewDefaults

    class StripChartInteractiveViewDefaults extends Defaults implements Serializable
    serialVersionUID:
      2247370679260844812L

  - ### Class weka.gui.knowledgeflow.steps.SubstringLabelerStepEditorDialog

    class SubstringLabelerStepEditorDialog extends StepEditorDialog implements Serializable
    serialVersionUID:
      2386951012941540643L

    - #### Serialized Fields

      - ##### m_attListField

            EnvironmentField m_attListField

        Field for specifying the attributes to match on

      - ##### m_consumeNonMatchingCheck

            JCheckBox m_consumeNonMatchingCheck

        Checkbox for specifying that non-matching instances should be consumed rather than having the match attribute value set to missing value

      - ##### m_deleteBut

            JButton m_deleteBut

        Button for deleting a match rule

      - ##### m_downBut

            JButton m_downBut

        Button for moving a match rule down in the list

      - ##### m_ignoreCaseCheck

            JCheckBox m_ignoreCaseCheck

        Checkbox for specifying that case should be ignored when matching

      - ##### m_labelField

            EnvironmentField m_labelField

        Field for specifying the label to assign if match is positive

      - ##### m_list

            JList<SubstringLabelerRules.SubstringLabelerMatchRule> m_list

        Holds the list of match rules

      - ##### m_listModel

            DefaultListModel<SubstringLabelerRules.SubstringLabelerMatchRule> m_listModel

        List model

      - ##### m_matchAttNameField

            EnvironmentField m_matchAttNameField

        Field for specifying the name of the new attribute to create

      - ##### m_matchField

            EnvironmentField m_matchField

        Field for specifying the string/regex to match

      - ##### m_newBut

            JButton m_newBut

        Button for adding a new match rule

      - ##### m_nominalBinaryCheck

            JCheckBox m_nominalBinaryCheck

        Checkbox for making a binary label attribute into a nominal one (rather than numeric)

      - ##### m_regexCheck

            JCheckBox m_regexCheck

        Checkbox to specify that the match is a regex

      - ##### m_upBut

            JButton m_upBut

        Button for moving a match rule up in the list

  - ### Class weka.gui.knowledgeflow.steps.SubstringReplacerStepEditorDialog

    class SubstringReplacerStepEditorDialog extends StepEditorDialog implements Serializable
    serialVersionUID:
      7804721324137987443L

    - #### Serialized Fields

      - ##### m_attListField

            EnvironmentField m_attListField

        Field for specifying the attributes to match on

      - ##### m_deleteBut

            JButton m_deleteBut

        Button for deleting a match rule

      - ##### m_downBut

            JButton m_downBut

        Button for moving a match rule down in the list

      - ##### m_ignoreCaseCheck

            JCheckBox m_ignoreCaseCheck

        Checkbox for specifying that case should be ignored when matching

      - ##### m_list

            JList<SubstringReplacerRules.SubstringReplacerMatchRule> m_list

        Holds the list of match rules

      - ##### m_listModel

            DefaultListModel<SubstringReplacerRules.SubstringReplacerMatchRule> m_listModel

        List model

      - ##### m_matchField

            EnvironmentField m_matchField

        Field for specifying the string/regex to match

      - ##### m_newBut

            JButton m_newBut

        Button for adding a new match rule

      - ##### m_regexCheck

            JCheckBox m_regexCheck

        Checkbox to specify that the match is a regex

      - ##### m_replaceField

            EnvironmentField m_replaceField

        Field for specifying the value to replace a match with

      - ##### m_upBut

            JButton m_upBut

        Button for moving a match rule up in the list

  - ### Class weka.gui.knowledgeflow.steps.TextViewerInteractiveView

    class TextViewerInteractiveView extends BaseInteractiveViewer implements Serializable
    serialVersionUID:
      -3164518320257969282L

    - #### Serialized Fields

      - ##### m_clearButton

            JButton m_clearButton

        Button for clearing the results

      - ##### m_history

            ResultHistoryPanel m_history

        Holds the list of results

      - ##### m_outText

            JTextArea m_outText

        The main text output area

      - ##### m_textScroller

            JScrollPane m_textScroller

        Scroll panel for the text area

  - ### Class weka.gui.knowledgeflow.steps.TextViewerInteractiveView.TextViewerInteractiveViewDefaults

    class TextViewerInteractiveViewDefaults extends Defaults implements Serializable
    serialVersionUID:
      8361658568822013306L

- ## Package weka.gui.scripting

  - ### Class weka.gui.scripting.FileScriptingPanel

    class FileScriptingPanel extends ScriptingPanel implements Serializable
    serialVersionUID:
      1583670545010241816L

    - #### Serialized Fields

      - ##### m_AboutAction

            weka.gui.scripting.FileScriptingPanel.AboutAction m_AboutAction

        the about action.

      - ##### m_Actions

            HashMap<Object,Action> m_Actions

        for storing the actions under their name.

      - ##### m_Args

            String[] m_Args

        the commandline arguments to use.

      - ##### m_ArgsAction

            weka.gui.scripting.FileScriptingPanel.CommandlineArgsAction m_ArgsAction

        the arguments action.

      - ##### m_ClearOutputAction

            weka.gui.scripting.FileScriptingPanel.ClearOutputAction m_ClearOutputAction

        the clear output action.

      - ##### m_CopyAction

            Action m_CopyAction

        the copy action.

      - ##### m_CutAction

            Action m_CutAction

        the cut action.

      - ##### m_ExitAction

            weka.gui.scripting.FileScriptingPanel.ExitAction m_ExitAction

        the exit action.

      - ##### m_FileChooser

            WekaFileChooser m_FileChooser

        for loading/saving file.

      - ##### m_LabelInfo

            JLabel m_LabelInfo

        for informing the user.

      - ##### m_NewAction

            weka.gui.scripting.FileScriptingPanel.NewAction m_NewAction

        the new action.

      - ##### m_OpenAction

            weka.gui.scripting.FileScriptingPanel.OpenAction m_OpenAction

        the open action.

      - ##### m_OutputArea

            JTextArea m_OutputArea

        the output area.

      - ##### m_PasteAction

            Action m_PasteAction

        the paste action.

      - ##### m_PrintAction

            weka.gui.scripting.FileScriptingPanel.PrintAction m_PrintAction

        the Print action.

      - ##### m_RedoAction

            weka.gui.scripting.FileScriptingPanel.RedoAction m_RedoAction

        the redo action.

      - ##### m_SaveAction

            weka.gui.scripting.FileScriptingPanel.SaveAction m_SaveAction

        the Save action.

      - ##### m_SaveAsAction

            weka.gui.scripting.FileScriptingPanel.SaveAction m_SaveAsAction

        the Save as action.

      - ##### m_Script

            Script m_Script

        the script.

      - ##### m_ScriptArea

            JTextArea m_ScriptArea

        the script area.

      - ##### m_StartAction

            weka.gui.scripting.FileScriptingPanel.StartAction m_StartAction

        the start action.

      - ##### m_StopAction

            weka.gui.scripting.FileScriptingPanel.StopAction m_StopAction

        the stop action.

      - ##### m_TextCode

            JTextPane m_TextCode

        the text pane with the code.

      - ##### m_TextOutput

            JTextPane m_TextOutput

        the text pane for the output.

      - ##### m_Undo

            UndoManager m_Undo

        the undo manager.

      - ##### m_UndoAction

            weka.gui.scripting.FileScriptingPanel.UndoAction m_UndoAction

        the undo action.

  - ### Class weka.gui.scripting.FileScriptingPanel.AboutAction

    class AboutAction extends FileScriptingPanel.BasicAction implements Serializable
    serialVersionUID:
      -6420463480569171227L

  - ### Class weka.gui.scripting.FileScriptingPanel.BasicAction

    class BasicAction extends AbstractAction implements Serializable
    serialVersionUID:
      2821117985661550385L

  - ### Class weka.gui.scripting.FileScriptingPanel.ClearOutputAction

    class ClearOutputAction extends FileScriptingPanel.BasicAction implements Serializable
    serialVersionUID:
      47986890456997211L

  - ### Class weka.gui.scripting.FileScriptingPanel.CommandlineArgsAction

    class CommandlineArgsAction extends FileScriptingPanel.BasicAction implements Serializable
    serialVersionUID:
      -3183470039010826204L

  - ### Class weka.gui.scripting.FileScriptingPanel.ExitAction

    class ExitAction extends FileScriptingPanel.BasicAction implements Serializable
    serialVersionUID:
      -5884709836238884180L

  - ### Class weka.gui.scripting.FileScriptingPanel.NewAction

    class NewAction extends FileScriptingPanel.BasicAction implements Serializable
    serialVersionUID:
      -8665722554539726090L

  - ### Class weka.gui.scripting.FileScriptingPanel.OpenAction

    class OpenAction extends FileScriptingPanel.BasicAction implements Serializable
    serialVersionUID:
      -4496148485267789162L

  - ### Class weka.gui.scripting.FileScriptingPanel.PrintAction

    class PrintAction extends FileScriptingPanel.BasicAction implements Serializable
    serialVersionUID:
      -6246539539545724632L

  - ### Class weka.gui.scripting.FileScriptingPanel.RedoAction

    class RedoAction extends FileScriptingPanel.BasicAction implements Serializable
    serialVersionUID:
      4533966901523279350L

  - ### Class weka.gui.scripting.FileScriptingPanel.SaveAction

    class SaveAction extends FileScriptingPanel.BasicAction implements Serializable
    serialVersionUID:
      -74651145892063975L

    - #### Serialized Fields

      - ##### m_ShowDialog

            boolean m_ShowDialog

        whether to bring up the save dialog all the time.

  - ### Class weka.gui.scripting.FileScriptingPanel.StartAction

    class StartAction extends FileScriptingPanel.BasicAction implements Serializable
    serialVersionUID:
      -7936456072955996220L

  - ### Class weka.gui.scripting.FileScriptingPanel.StopAction

    class StopAction extends FileScriptingPanel.BasicAction implements Serializable
    serialVersionUID:
      8764023289575718872L

  - ### Class weka.gui.scripting.FileScriptingPanel.UndoAction

    class UndoAction extends FileScriptingPanel.BasicAction implements Serializable
    serialVersionUID:
      4298096648424808522L

  - ### Class weka.gui.scripting.GroovyPanel

    class GroovyPanel extends FileScriptingPanel implements Serializable
    serialVersionUID:
      -3475707604414854111L

  - ### Class weka.gui.scripting.GroovyScript

    class GroovyScript extends Script implements Serializable
    serialVersionUID:
      -3708517162415549420L

  - ### Class weka.gui.scripting.JythonPanel

    class JythonPanel extends FileScriptingPanel implements Serializable
    serialVersionUID:
      -827358576217085413L

  - ### Class weka.gui.scripting.JythonScript

    class JythonScript extends Script implements Serializable
    serialVersionUID:
      3469648507172973169L

  - ### Class weka.gui.scripting.Script

    class Script extends Object implements Serializable
    serialVersionUID:
      5053328052680586401L

    - #### Serialized Fields

      - ##### m_Document

            Document m_Document

        the document this script is a wrapper around.

      - ##### m_Filename

            File m_Filename

        the filename of the script.

      - ##### m_FinishedListeners

            HashSet<ScriptExecutionListener> m_FinishedListeners

        optional listeners when the script finishes.

      - ##### m_Modified

            boolean m_Modified

        whether the script is modified.

      - ##### m_NewLine

            String m_NewLine

        the newline used on this platform.

  - ### Class weka.gui.scripting.ScriptingPanel

    class ScriptingPanel extends JPanel implements Serializable
    serialVersionUID:
      7593091442691911406L

    - #### Serialized Fields

      - ##### m_Debug

            boolean m_Debug

        whether debug mode is on.

      - ##### m_ErrPrintStream

            PrintStream m_ErrPrintStream

        The print stream that is wrapped around the piped error output stream. We need a a reference to it at the class level so that we can remove it from the tee when the panel is terminated.

      - ##### m_ErrRedirector

            ReaderToTextPane m_ErrRedirector

        The thread that sends output from m_POE to the output box.

      - ##### m_ErrTee

            Tee m_ErrTee

        The Tee that the err stream will be part of. We need a reference to it at the class level so that we can remove the stream from it when the panel is terminated.

      - ##### m_OutRedirector

            ReaderToTextPane m_OutRedirector

        The thread that sends output from m_POO to the output box.

      - ##### m_POE

            PipedOutputStream m_POE

        The new output stream for System.err.

      - ##### m_POO

            PipedOutputStream m_POO

        The new output stream for System.out.

      - ##### m_PrintStream

            PrintStream m_PrintStream

        The print stream that is wrapped around the piped output stream. We need a a reference to it at the class level so that we can remove it from the tee when the panel is terminated.

      - ##### m_Tee

            Tee m_Tee

        The Tee that the output stream will be part of. We need a reference to it at the class level so that we can remove the stream from it when the panel is terminated.

      - ##### m_TitleUpdatedListeners

            HashSet<TitleUpdatedListener> m_TitleUpdatedListeners

        the listeners for the changes in the title.

  - ### Class weka.gui.scripting.SyntaxDocument

    class SyntaxDocument extends DefaultStyledDocument implements Serializable
    serialVersionUID:
      -3642426465631271381L

    - #### Serialized Fields

      - ##### m_AddMatchingEndBlocks

            boolean m_AddMatchingEndBlocks

        whether to add matching brackets.

      - ##### m_BackgroundColor

            Color m_BackgroundColor

        the background color.

      - ##### m_BlockEnd

            String m_BlockEnd

        the end of a block.

      - ##### m_BlockStart

            String m_BlockStart

        the start of a block.

      - ##### m_CaseSensitive

            boolean m_CaseSensitive

        whether keywords are case-sensitive.

      - ##### m_Delimiters

            String m_Delimiters

        the delimiters.

      - ##### m_FontName

            String m_FontName

        the font name.

      - ##### m_FontSize

            int m_FontSize

        the font size.

      - ##### m_Indentation

            String m_Indentation

        the number of spaces used for indentation.

      - ##### m_InsideMultiLineComment

            boolean m_InsideMultiLineComment

        whether we're currently in a multi-line comment.

      - ##### m_Keywords

            HashMap<String,MutableAttributeSet> m_Keywords

        the keywords.

      - ##### m_MultiLineComment

            boolean m_MultiLineComment

        whether multi-line comments are enabled.

      - ##### m_MultiLineCommentEnd

            String m_MultiLineCommentEnd

        the multi-line comment end.

      - ##### m_MultiLineCommentStart

            String m_MultiLineCommentStart

        the multi-line comment start.

      - ##### m_QuoteDelimiters

            String m_QuoteDelimiters

        the quote delimiter.

      - ##### m_QuoteEscape

            String m_QuoteEscape

        the quote escape.

      - ##### m_RootElement

            Element m_RootElement

        the root element.

      - ##### m_Self

            DefaultStyledDocument m_Self

        the document.

      - ##### m_SingleLineCommentStart

            String m_SingleLineCommentStart

        the single-line comment start.

      - ##### m_UseBlanks

            boolean m_UseBlanks

        whether to use blanks instead of tabs.

- ## Package weka.gui.scripting.event

  - ### Class weka.gui.scripting.event.ScriptExecutionEvent

    class ScriptExecutionEvent extends EventObject implements Serializable
    serialVersionUID:
      -8357216611114356632L

    - #### Serialized Fields

      - ##### m_Additional

            Object m_Additional

        optional additional information.

      - ##### m_Type

            ScriptExecutionEvent.Type m_Type

        the type of event.

  - ### Class weka.gui.scripting.event.TitleUpdatedEvent

    class TitleUpdatedEvent extends EventObject implements Serializable
    serialVersionUID:
      4971569742479666535L

- ## Package weka.gui.simplecli

  - ### Class weka.gui.simplecli.AbstractCommand

    class AbstractCommand extends Object implements Serializable

    - #### Serialized Fields

      - ##### m_Owner

            SimpleCLIPanel m_Owner

        the owner.

  - ### Class weka.gui.simplecli.Capabilities

    class Capabilities extends AbstractCommand implements Serializable

  - ### Class weka.gui.simplecli.Cls

    class Cls extends AbstractCommand implements Serializable

  - ### Class weka.gui.simplecli.Echo

    class Echo extends AbstractCommand implements Serializable

  - ### Class weka.gui.simplecli.Exit

    class Exit extends AbstractCommand implements Serializable

  - ### Class weka.gui.simplecli.Help

    class Help extends AbstractCommand implements Serializable

  - ### Class weka.gui.simplecli.History

    class History extends AbstractCommand implements Serializable

  - ### Class weka.gui.simplecli.Java

    class Java extends AbstractCommand implements Serializable

  - ### Class weka.gui.simplecli.Kill

    class Kill extends AbstractCommand implements Serializable

  - ### Class weka.gui.simplecli.Script

    class Script extends AbstractCommand implements Serializable

  - ### Class weka.gui.simplecli.Set

    class Set extends AbstractCommand implements Serializable

  - ### Class weka.gui.simplecli.Unset

    class Unset extends AbstractCommand implements Serializable

- ## Package weka.gui.sql

  - ### Class weka.gui.sql.ConnectionPanel

    class ConnectionPanel extends JPanel implements Serializable
    serialVersionUID:
      3499317023969723490L

    - #### Serialized Fields

      - ##### m_ButtonConnect

            JButton m_ButtonConnect

        the button for connecting to the database.

      - ##### m_ButtonDatabase

            JButton m_ButtonDatabase

        the button for the DB-Dialog.

      - ##### m_ButtonHistory

            JButton m_ButtonHistory

        the button for the history.

      - ##### m_ButtonSetup

            JButton m_ButtonSetup

        the button for the setup.

      - ##### m_ConnectionListeners

            HashSet<ConnectionListener> m_ConnectionListeners

        the connection listeners.

      - ##### m_DbDialog

            DatabaseConnectionDialog m_DbDialog

        the database connection dialog.

      - ##### m_DbUtils

            DbUtils m_DbUtils

        for connecting to the database.

      - ##### m_History

            DefaultListModel m_History

        the history of connections.

      - ##### m_HistoryChangedListeners

            HashSet<HistoryChangedListener> m_HistoryChangedListeners

        the history listeners.

      - ##### m_LabelURL

            JLabel m_LabelURL

        the label for the URL.

      - ##### m_Parent

            JFrame m_Parent

        the parent frame.

      - ##### m_Password

            String m_Password

        the password to use for connecting to the DB.

      - ##### m_SetupFileChooser

            WekaFileChooser m_SetupFileChooser

        the file chooser for the setup files.

      - ##### m_TextURL

            JTextField m_TextURL

        the textfield for the URL.

      - ##### m_URL

            String m_URL

        the URL to use.

      - ##### m_User

            String m_User

        the user to use for connecting to the DB.

  - ### Class weka.gui.sql.DbUtils

    class DbUtils extends DatabaseUtils implements Serializable
    serialVersionUID:
      103748569037426479L

  - ### Class weka.gui.sql.InfoPanel

    class InfoPanel extends JPanel implements Serializable
    serialVersionUID:
      -7701133696481997973L

    - #### Serialized Fields

      - ##### m_ButtonClear

            JButton m_ButtonClear

        the button to clear the area

      - ##### m_ButtonCopy

            JButton m_ButtonCopy

        the button to copy the selected message

      - ##### m_Info

            JList m_Info

        the list the contains the messages

      - ##### m_Model

            DefaultListModel m_Model

        the model for the list

      - ##### m_Parent

            JFrame m_Parent

        the parent of this panel

  - ### Class weka.gui.sql.InfoPanelCellRenderer

    class InfoPanelCellRenderer extends JLabel implements Serializable
    serialVersionUID:
      -533380118807178531L

  - ### Class weka.gui.sql.QueryPanel

    class QueryPanel extends JPanel implements Serializable
    serialVersionUID:
      4348967824619706636L

    - #### Serialized Fields

      - ##### m_ButtonClear

            JButton m_ButtonClear

        the clear button.

      - ##### m_ButtonExecute

            JButton m_ButtonExecute

        the execute button.

      - ##### m_ButtonHistory

            JButton m_ButtonHistory

        the history button.

      - ##### m_Connected

            boolean m_Connected

        whether we have a connection to a database or not.

      - ##### m_DbUtils

            DbUtils m_DbUtils

        for working on the database.

      - ##### m_History

            DefaultListModel m_History

        the query history.

      - ##### m_HistoryChangedListeners

            HashSet<HistoryChangedListener> m_HistoryChangedListeners

        the history listeners.

      - ##### m_Parent

            JFrame m_Parent

        the parent of this panel.

      - ##### m_QueryExecuteListeners

            HashSet<QueryExecuteListener> m_QueryExecuteListeners

        the connection listeners.

      - ##### m_SpinnerMaxRows

            JSpinner m_SpinnerMaxRows

        the spinner for the maximum number of rows.

      - ##### m_TextQuery

            JTextArea m_TextQuery

        the textarea for the query.

  - ### Class weka.gui.sql.ResultPanel

    class ResultPanel extends JPanel implements Serializable
    serialVersionUID:
      278654800344034571L

    - #### Serialized Fields

      - ##### m_ButtonClose

            JButton m_ButtonClose

        the close button

      - ##### m_ButtonCloseAll

            JButton m_ButtonCloseAll

        the close all button

      - ##### m_ButtonCopyQuery

            JButton m_ButtonCopyQuery

        the button that copies the query into the QueryPanel

      - ##### m_ButtonOptWidth

            JButton m_ButtonOptWidth

        the button for the optimal column width of the current table

      - ##### m_Listeners

            HashSet<ResultChangedListener> m_Listeners

        the result change listeners

      - ##### m_NameCounter

            int m_NameCounter

        the counter for the tab names

      - ##### m_Parent

            JFrame m_Parent

        the parent of this panel

      - ##### m_QueryPanel

            QueryPanel m_QueryPanel

        the panel where to output the queries

      - ##### m_TabbedPane

            JTabbedPane m_TabbedPane

        the tabbed pane for the results

  - ### Class weka.gui.sql.ResultSetTable

    class ResultSetTable extends JTable implements Serializable
    serialVersionUID:
      -3391076671854464137L

    - #### Serialized Fields

      - ##### m_Password

            String m_Password

        the password that was used to connect to the DB

      - ##### m_Query

            String m_Query

        the query the table model is based on

      - ##### m_URL

            String m_URL

        the connect string with which the query was run

      - ##### m_User

            String m_User

        the user that was used to connect to the DB

  - ### Class weka.gui.sql.ResultSetTableCellRenderer

    class ResultSetTableCellRenderer extends DefaultTableCellRenderer implements Serializable
    serialVersionUID:
      -8106963669703497351L

    - #### Serialized Fields

      - ##### missingColor

            Color missingColor

      - ##### missingColorSelected

            Color missingColorSelected

  - ### Class weka.gui.sql.SqlViewer

    class SqlViewer extends JPanel implements Serializable
    serialVersionUID:
      -4395028775566514329L

    - #### Serialized Fields

      - ##### m_ConnectionPanel

            ConnectionPanel m_ConnectionPanel

        the connection panel.

      - ##### m_History

            Properties m_History

        stores the history.

      - ##### m_InfoPanel

            InfoPanel m_InfoPanel

        the info panel.

      - ##### m_Parent

            JFrame m_Parent

        the parent of this panel.

      - ##### m_Password

            String m_Password

        the password that was used to connect to the DB.

      - ##### m_Query

            String m_Query

        the currently selected query.

      - ##### m_QueryPanel

            QueryPanel m_QueryPanel

        the query panel.

      - ##### m_ResultPanel

            ResultPanel m_ResultPanel

        the result panel.

      - ##### m_URL

            String m_URL

        the connect string with which the query was run.

      - ##### m_User

            String m_User

        the user that was used to connect to the DB.

  - ### Class weka.gui.sql.SqlViewerDialog

    class SqlViewerDialog extends JDialog implements Serializable
    serialVersionUID:
      -31619864037233099L

    - #### Serialized Fields

      - ##### m_ButtonCancel

            JButton m_ButtonCancel

        the Cancel button.

      - ##### m_ButtonOK

            JButton m_ButtonOK

        the OK button.

      - ##### m_CheckBoxSparseData

            JCheckBox m_CheckBoxSparseData

        whether to return sparse instances or not.

      - ##### m_LabelQuery

            JLabel m_LabelQuery

        displays the current query.

      - ##### m_PanelButtons

            JPanel m_PanelButtons

        the panel for the buttons.

      - ##### m_Parent

            JFrame m_Parent

        the parent frame.

      - ##### m_Password

            String m_Password

        the password that was used to connect to the DB.

      - ##### m_Query

            String m_Query

        the currently selected query.

      - ##### m_ReturnValue

            int m_ReturnValue

        the return value.

      - ##### m_URL

            String m_URL

        the connect string with which the query was run.

      - ##### m_User

            String m_User

        the user that was used to connect to the DB.

      - ##### m_Viewer

            SqlViewer m_Viewer

        the SQL panel.

- ## Package weka.gui.sql.event

  - ### Class weka.gui.sql.event.ConnectionEvent

    class ConnectionEvent extends EventObject implements Serializable
    serialVersionUID:
      5420308930427835037L

    - #### Serialized Fields

      - ##### m_DbUtils

            DbUtils m_DbUtils

        the databaseutils instance reponsible for the connection

      - ##### m_Exception

            Exception m_Exception

        a possible exception that occurred if not successful

      - ##### m_Type

            int m_Type

        the type of event, CONNECT or DISCONNECT

  - ### Class weka.gui.sql.event.HistoryChangedEvent

    class HistoryChangedEvent extends EventObject implements Serializable
    serialVersionUID:
      7476087315774869973L

    - #### Serialized Fields

      - ##### m_History

            DefaultListModel m_History

        the history model

      - ##### m_HistoryName

            String m_HistoryName

        the name of the history

  - ### Class weka.gui.sql.event.QueryExecuteEvent

    class QueryExecuteEvent extends EventObject implements Serializable
    serialVersionUID:
      -5556385019954730740L

    - #### Serialized Fields

      - ##### m_DbUtils

            DbUtils m_DbUtils

        the Db utils instance for the current DB connection

      - ##### m_Exception

            Exception m_Exception

        a possible exception, if the query failed

      - ##### m_MaxRows

            int m_MaxRows

        the maximum number of rows to retrieve

      - ##### m_Query

            String m_Query

        the query that was executed

      - ##### m_ResultSet

            ResultSet m_ResultSet

        the produced ResultSet, if any

  - ### Class weka.gui.sql.event.ResultChangedEvent

    class ResultChangedEvent extends EventObject implements Serializable
    serialVersionUID:
      36042516077236111L

    - #### Serialized Fields

      - ##### m_Password

            String m_Password

        the password that was used to connect to the DB

      - ##### m_Query

            String m_Query

        the query that is associated with the active result table

      - ##### m_URL

            String m_URL

        the connect string with which the query was run

      - ##### m_User

            String m_User

        the user that was used to connect to the DB

- ## Package weka.gui.streams

  - ### Class weka.gui.streams.InstanceCounter

    class InstanceCounter extends JPanel implements Serializable
    serialVersionUID:
      -6084967152645935934L

    - #### Serialized Fields

      - ##### m_Count

            int m_Count

      - ##### m_Count_Lab

            JLabel m_Count_Lab

      - ##### m_Debug

            boolean m_Debug

  - ### Class weka.gui.streams.InstanceEvent

    class InstanceEvent extends EventObject implements Serializable
    serialVersionUID:
      3207259868110667379L

    - #### Serialized Fields

      - ##### m_ID

            int m_ID

  - ### Class weka.gui.streams.InstanceJoiner

    class InstanceJoiner extends Object implements Serializable
    serialVersionUID:
      -6529972700291329656L

    - #### Serialized Fields

      - ##### b_Debug

            boolean b_Debug

        Debugging mode

      - ##### b_FirstInputFinished

            boolean b_FirstInputFinished

        Whether the first input batch has finished

      - ##### listeners

            Vector<InstanceListener> listeners

        The listeners

      - ##### m_InputFormat

            Instances m_InputFormat

        The input format for instances

      - ##### m_OutputInstance

            Instance m_OutputInstance

        The current output instance

  - ### Class weka.gui.streams.InstanceLoader

    class InstanceLoader extends JPanel implements Serializable
    serialVersionUID:
      -8725567310271862492L

    - #### Serialized Fields

      - ##### m_Debug

            boolean m_Debug

      - ##### m_FileNameTex

            JTextField m_FileNameTex

      - ##### m_Listeners

            Vector<InstanceListener> m_Listeners

      - ##### m_LoaderThread

            Thread m_LoaderThread

      - ##### m_OutputInstance

            Instance m_OutputInstance

      - ##### m_OutputInstances

            Instances m_OutputInstances

      - ##### m_StartBut

            JButton m_StartBut

  - ### Class weka.gui.streams.InstanceSavePanel

    class InstanceSavePanel extends Panel implements Serializable
    serialVersionUID:
      -6061005366989295026L

    - #### Serialized Fields

      - ##### arffFile_Tex

            TextField arffFile_Tex

      - ##### b_Debug

            boolean b_Debug

      - ##### count_Lab

            Label count_Lab

      - ##### m_Count

            int m_Count

      - ##### outputWriter

            PrintWriter outputWriter

  - ### Class weka.gui.streams.InstanceTable

    class InstanceTable extends JPanel implements Serializable
    serialVersionUID:
      -2462533698100834803L

    - #### Serialized Fields

      - ##### m_Debug

            boolean m_Debug

      - ##### m_Instances

            Instances m_Instances

      - ##### m_InstanceTable

            JTable m_InstanceTable

  - ### Class weka.gui.streams.InstanceViewer

    class InstanceViewer extends JPanel implements Serializable
    serialVersionUID:
      -4925729441294121772L

    - #### Serialized Fields

      - ##### m_Clear

            boolean m_Clear

      - ##### m_Debug

            boolean m_Debug

      - ##### m_OutputTex

            JTextArea m_OutputTex

      - ##### m_UpdateString

            String m_UpdateString

- ## Package weka.gui.treevisualizer

  - ### Class weka.gui.treevisualizer.TreeVisualizer

    class TreeVisualizer extends PrintablePanel implements Serializable
    serialVersionUID:
      -8668637962504080749L

    - #### Serialized Fields

      - ##### m_accept

            JMenuItem m_accept

        An option on the win menu.

      - ##### m_autoScale

            JMenuItem m_autoScale

        An option on the win_menu

      - ##### m_BackgroundColor

            Color m_BackgroundColor

        the background color.

      - ##### m_classifyChild

            JMenuItem m_classifyChild

        Use this to have J48 classify this node.

      - ##### m_clickAvailable

            boolean m_clickAvailable

        A variable used to determine for the clicked method if any other mouse state has already taken place.

      - ##### m_currentFont

            Font m_currentFont

        The font used to display the tree.

      - ##### m_edges

            weka.gui.treevisualizer.TreeVisualizer.EdgeInfo[] m_edges

        An array with the Edges sorted into it and display information about the Edges.

      - ##### m_fitToScreen

            JMenuItem m_fitToScreen

        An option on the win_menu

      - ##### m_focusNode

            int m_focusNode

        The subscript for the currently selected node (this is an internal thing, so the user is unaware of this).

      - ##### m_FontColor

            Color m_FontColor

        the font color.

      - ##### m_fontSize

            FontMetrics m_fontSize

        The size information for the current font.

      - ##### m_frameLimiter

            Timer m_frameLimiter

        A timer to keep the frame rate constant.

      - ##### m_highlightNode

            int m_highlightNode

        The Node the user is currently focused on , this is similar to focus node except that it is used by other classes rather than this one.

      - ##### m_LineColor

            Color m_LineColor

        the line color.

      - ##### m_listener

            TreeDisplayListener m_listener

      - ##### m_mouseState

            int m_mouseState

        Describes the action the user is performing.

      - ##### m_newMousePos

            Dimension m_newMousePos

        A variable used to tag the most current point of a user action.

      - ##### m_NodeColor

            Color m_NodeColor

        the node color.

      - ##### m_nodeMenu

            JPopupMenu m_nodeMenu

        A right or middle click popup menu for nodes.

      - ##### m_nodes

            weka.gui.treevisualizer.TreeVisualizer.NodeInfo[] m_nodes

        An array with the Nodes sorted into it and display information about the Nodes.

      - ##### m_numLevels

            int m_numLevels

        The number of levels in the tree.

      - ##### m_numNodes

            int m_numNodes

        The number of Nodes in the tree.

      - ##### m_nViewPos

            Dimension m_nViewPos

        A variable used to remember the desired view pos.

      - ##### m_nViewSize

            Dimension m_nViewSize

        A variable used to remember the desired tree size.

      - ##### m_oldMousePos

            Dimension m_oldMousePos

        A variable used to tag the start pos of a user action.

      - ##### m_placer

            NodePlace m_placer

        The placement algorithm for the Node structure.

      - ##### m_remChildren

            JMenuItem m_remChildren

        Similar to add children but now it removes children.

      - ##### m_scaling

            int m_scaling

        The number of frames left to calculate.

      - ##### m_selectFont

            JMenu m_selectFont

        A sub group on the win_menu

      - ##### m_selectFontGroup

            ButtonGroup m_selectFontGroup

        A grouping for the font choices

      - ##### m_sendInstances

            JMenuItem m_sendInstances

        Use this to dump the instances from this node to the vis panel.

      - ##### m_ShowBorder

            boolean m_ShowBorder

        whether to show the border or not.

      - ##### m_size1

            JRadioButtonMenuItem m_size1

        A font choice.

      - ##### m_size10

            JRadioButtonMenuItem m_size10

        A font choice.

      - ##### m_size12

            JRadioButtonMenuItem m_size12

        A font choice.

      - ##### m_size14

            JRadioButtonMenuItem m_size14

        A font choice.

      - ##### m_size16

            JRadioButtonMenuItem m_size16

        A font choice.

      - ##### m_size18

            JRadioButtonMenuItem m_size18

        A font choice.

      - ##### m_size2

            JRadioButtonMenuItem m_size2

        A font choice.

      - ##### m_size20

            JRadioButtonMenuItem m_size20

        A font choice.

      - ##### m_size22

            JRadioButtonMenuItem m_size22

        A font choice.

      - ##### m_size24

            JRadioButtonMenuItem m_size24

        A font choice.

      - ##### m_size4

            JRadioButtonMenuItem m_size4

        A font choice.

      - ##### m_size6

            JRadioButtonMenuItem m_size6

        A font choice.

      - ##### m_size8

            JRadioButtonMenuItem m_size8

        A font choice.

      - ##### m_topN

            JMenuItem m_topN

        An option on the win_menu

      - ##### m_topNode

            Node m_topNode

        The top Node.

      - ##### m_viewPos

            Dimension m_viewPos

        The postion of the view relative to the tree.

      - ##### m_viewSize

            Dimension m_viewSize

        The size of the tree in pixels.

      - ##### m_visualise

            JMenuItem m_visualise

        A visualize choice for the node, may not be available.

      - ##### m_winMenu

            JPopupMenu m_winMenu

        A right (or middle) click popup menu.

      - ##### m_ZoomBoxColor

            Color m_ZoomBoxColor

        the color of the zoombox.

      - ##### m_ZoomBoxXORColor

            Color m_ZoomBoxXORColor

        the XOR color of the zoombox.

- ## Package weka.gui.visualize

  - ### Class weka.gui.visualize.AttributePanel

    class AttributePanel extends JScrollPane implements Serializable
    serialVersionUID:
      3533330317806757814L

    - #### Serialized Fields

      - ##### m_backgroundColor

            Color m_backgroundColor

        If set, it allows this panel to avoid setting a color in the color list that is equal to the background color

      - ##### m_barColour

            Color m_barColour

        The default colour to use for the background of the bars if a colour is not defined in Visualize.props

      - ##### m_cIndex

            int m_cIndex

      - ##### m_colorList

            ArrayList<Color> m_colorList

        The colour map to use for colouring points

      - ##### m_DefaultColors

            Color[] m_DefaultColors

        default colours for colouring discrete class

      - ##### m_heights

            int[] m_heights

        Holds the random height for each instance.

      - ##### m_Listeners

            ArrayList<AttributePanelListener> m_Listeners

        The list of things listening to this panel

      - ##### m_maxC

            double m_maxC

        Holds the min and max values of the colouring attributes

      - ##### m_minC

            double m_minC

      - ##### m_plotInstances

            Instances m_plotInstances

        The instances to be plotted

      - ##### m_span

            JPanel m_span

        The container window for the attribute bars, and also where the X,Y or B get printed.

      - ##### m_xIndex

            int m_xIndex

      - ##### m_yIndex

            int m_yIndex

  - ### Class weka.gui.visualize.AttributePanel.AttributeSpacing

    class AttributeSpacing extends JPanel implements Serializable
    serialVersionUID:
      7220615894321679898L

    - #### Serialized Fields

      - ##### m_attrib

            Attribute m_attrib

        The attribute itself.

      - ##### m_attribIndex

            int m_attribIndex

        The index for this attribute.

      - ##### m_cached

            int[] m_cached

        The x position of each point.

      - ##### m_maxVal

            double m_maxVal

        The min and max values for this attribute.

      - ##### m_minVal

            double m_minVal

      - ##### m_oldWidth

            int m_oldWidth

        Used to determine if the positions need to be recalculated.

      - ##### m_pointDrawn

            boolean[][] m_pointDrawn

        A temporary array used to strike any instances that would be drawn redundantly.

  - ### Class weka.gui.visualize.ClassPanel

    class ClassPanel extends JPanel implements Serializable
    serialVersionUID:
      -7969401840501661430L

    - #### Serialized Fields

      - ##### m_backgroundColor

            Color m_backgroundColor

        if set, it allows this panel to steer away from setting up a color in the color list that is equal to the background color

      - ##### m_cIndex

            int m_cIndex

        Index of the colouring attribute

      - ##### m_colorList

            ArrayList<Color> m_colorList

        the list of colours to use for colouring nominal attribute labels

      - ##### m_ColourChangeListeners

            ArrayList<ActionListener> m_ColourChangeListeners

        An optional list of listeners who want to know when a colour changes. Listeners are notified via an ActionEvent

      - ##### m_DefaultColors

            Color[] m_DefaultColors

        default colours for colouring discrete class

      - ##### m_HorizontalPad

            int m_HorizontalPad

        The amount of space to leave either side of the legend

      - ##### m_Instances

            Instances m_Instances

        Instances being plotted

      - ##### m_isEnabled

            boolean m_isEnabled

        True when the panel has been enabled (ie after setNumeric or setNominal has been called

      - ##### m_isNumeric

            boolean m_isNumeric

        True if the colouring attribute is numeric

      - ##### m_labelFont

            Font m_labelFont

        The font used in labeling

      - ##### m_labelMetrics

            FontMetrics m_labelMetrics

        Font metrics

      - ##### m_maxC

            double m_maxC

        The maximum value for the colouring attribute

      - ##### m_minC

            double m_minC

        The minimum value for the colouring attribute

      - ##### m_oldWidth

            int m_oldWidth

        The old width.

      - ##### m_precisionC

            int m_precisionC

        The precision with which to display real values

      - ##### m_Repainters

            ArrayList<Component> m_Repainters

        An optional list of Components that use the colour list maintained by this class. If the user changes a colour using the colour chooser, then these components need to be repainted in order to display the change

      - ##### m_spectrumHeight

            int m_spectrumHeight

        The height of the spectrum for numeric class

      - ##### m_tickSize

            int m_tickSize

        The size of the ticks

  - ### Class weka.gui.visualize.InstanceInfoFrame

    class InstanceInfoFrame extends JFrame implements Serializable
    serialVersionUID:
      4684184733677263009L

    - #### Serialized Fields

      - ##### m_Data

            Vector<Instances> m_Data

        the underlying data.

      - ##### m_TextInfo

            JTextArea m_TextInfo

        the text area for displaying the info.

  - ### Class weka.gui.visualize.LegendPanel

    class LegendPanel extends JScrollPane implements Serializable
    serialVersionUID:
      -1262384440543001505L

    - #### Serialized Fields

      - ##### m_plots

            ArrayList<PlotData2D> m_plots

        the list of plot elements

      - ##### m_Repainters

            ArrayList<Component> m_Repainters

        a list of components that need to be repainted when a colour is changed

      - ##### m_span

            JPanel m_span

        the panel that contains the legend entries

  - ### Class weka.gui.visualize.LegendPanel.LegendEntry

    class LegendEntry extends JPanel implements Serializable
    serialVersionUID:
      3879990289042935670L

    - #### Serialized Fields

      - ##### m_dataIndex

            int m_dataIndex

        the index (in the list of plots) of the data for this legend--- used to draw the correct shape for this data

      - ##### m_legendText

            JLabel m_legendText

        the text part of this legend

      - ##### m_plotData

            PlotData2D m_plotData

        the data for this legend entry

      - ##### m_pointShape

            JPanel m_pointShape

        displays the point shape associated with this legend entry

  - ### Class weka.gui.visualize.MatrixPanel

    class MatrixPanel extends JPanel implements Serializable
    serialVersionUID:
      -1232642719869188740L

    - #### Serialized Fields

      - ##### datapointSize

            int datapointSize

        This stores the size of the datapoint

      - ##### f

            Font f

        font used in column and row names

      - ##### fontColor

            Color fontColor

        color for the font used in column and row names

      - ##### jitterVals

            int[][] jitterVals

        Array containing precalculated jitter values

      - ##### jp

            JSplitPane jp

        Split pane for splitting the matrix and the buttons and bars

      - ##### m_attribList

            JList m_attribList

        The list for selecting the attributes to display the plot matrix

      - ##### m_backgroundColor

            Color m_backgroundColor

        For the background of the little plots

      - ##### m_classAttrib

            JComboBox m_classAttrib

        The combo box to allow user to select the colouring attribute

      - ##### m_classIndex

            int m_classIndex

        This contains the index of the currently selected colouring attribute

      - ##### m_clearOSIPlottedCells

            boolean m_clearOSIPlottedCells

      - ##### m_colorList

            ArrayList<Color> m_colorList

        Contains discrete colours for colouring for nominal attributes

      - ##### m_cp

            ClassPanel m_cp

        The panel that displays the legend of the colouring attribute

      - ##### m_data

            Instances m_data

        The dataset for which this panel will display the plot matrix for

      - ##### m_fastScroll

            JCheckBox m_fastScroll

      - ##### m_jitter

            JSlider m_jitter

        The slider to add jitter to the plots

      - ##### m_js

            JScrollPane m_js

        The scroll pane to scrolling the matrix

      - ##### m_missing

            boolean[][] m_missing

        Contains true for each attribute value (only the selected attributes+class attribute) that is missing, for each instance. m_missing[i][j] == true if m_selectedAttribs[j] is missing in instance i. m_missing[i][m_missing[].length-1] == true if class value is missing in instance i.

      - ##### m_plotLBSizeD

            Dimension m_plotLBSizeD

        Stores the maximum size for PlotSize label to keep it's size constant

      - ##### m_plotSize

            JSlider m_plotSize

        The slider to adjust the size of the cells in the matrix

      - ##### m_plotSizeLb

            JLabel m_plotSizeLb

        Displays the current size beside the slider bar for cell size

      - ##### m_plotsPanel

            weka.gui.visualize.MatrixPanel.Plot m_plotsPanel

        The that panel contains the actual matrix

      - ##### m_plottedCells

            boolean[][] m_plottedCells

      - ##### m_pointColors

            int[] m_pointColors

        This is an array cache for the colour of each of the instances depending on the colouring attribute. If the colouring attribute is nominal then it contains the index of the colour in our colour list. Otherwise, for numeric colouring attribute, it contains the precalculated red component for each instance's colour

      - ##### m_pointLBSizeD

            Dimension m_pointLBSizeD

        Stores the maximum size for PointSize label to keep it's size constant

      - ##### m_points

            int[][] m_points

        This is a local array cache for all the instance values for faster rendering

      - ##### m_pointSize

            JSlider m_pointSize

        The slider to adjust the size of the datapoints

      - ##### m_pointSizeLb

            JLabel m_pointSizeLb

        Displays the current size beside the slider bar for point size

      - ##### m_previousPercent

            double m_previousPercent

      - ##### m_regenerateOSI

            boolean m_regenerateOSI

      - ##### m_resampleBt

            JButton m_resampleBt

        The label for resample percentage

      - ##### m_resamplePercent

            JTextField m_resamplePercent

        The text area for percentage to resample data

      - ##### m_rseed

            JTextField m_rseed

        Random seed for random subsample

      - ##### m_selAttrib

            JButton m_selAttrib

        The button to display a window to select attributes

      - ##### m_selectedAttribs

            int[] m_selectedAttribs

        This array contains the indices of the attributes currently selected

      - ##### m_settings

            Settings m_settings

        Settings (if available) to pass through to the VisualizePanels

      - ##### m_settingsOwnerID

            String m_settingsOwnerID

        ID of the owner (perspective, panel etc.) under which to lookup our settings

      - ##### m_type

            int[] m_type

        This array contains for the classAttribute:
        m_type[0] = [type of attribute, nominal, string or numeric]
        m_type[1] = [number of discrete values of nominal or string attribute
        or same as m_type[0] for numeric attribute]

      - ##### m_updateBt

            JButton m_updateBt

        The button that updates the display to reflect the changes made by the user. E.g. changed attribute set for the matrix

      - ##### optionsPanel

            JPanel optionsPanel

        The panel that contains all the buttons and tools, i.e. resize, jitter bars and sub-sampling buttons etc on the bottom of the panel

      - ##### rnd

            Random rnd

        For adding random jitter

  - ### Class weka.gui.visualize.Plot2D

    class Plot2D extends JPanel implements Serializable
    serialVersionUID:
      -1673162410856660442L

    - #### Serialized Fields

      - ##### m_axisChanged

            boolean m_axisChanged

        if the user changes attribute assigned to an axis

      - ##### m_axisColour

            Color m_axisColour

        Default colour for the axis

      - ##### m_axisPad

            int m_axisPad

        Axis padding

      - ##### m_backgroundColour

            Color m_backgroundColour

        Default colour for the plot background

      - ##### m_cIndex

            int m_cIndex

      - ##### m_colorList

            ArrayList<Color> m_colorList

        The list of the colors used

      - ##### m_DefaultColors

            Color[] m_DefaultColors

        default colours for colouring discrete class

      - ##### m_drawnPoints

            int[][] m_drawnPoints

        An array used to show if a point is hidden or not. This is used for speeding up the drawing of the plot panel although I am not sure how much performance this grants over not having it.

      - ##### m_InstanceInfo

            JFrame m_InstanceInfo

        For popping up text info on data points

      - ##### m_InstanceInfoFrameClass

            Class<?> m_InstanceInfoFrameClass

        the class for displaying instance info.

      - ##### m_JitterVal

            int m_JitterVal

        the level of jitter

      - ##### m_JRand

            Random m_JRand

        random values for perterbing the data points

      - ##### m_labelFont

            Font m_labelFont

        Font for labels

      - ##### m_labelMetrics

            FontMetrics m_labelMetrics

      - ##### m_masterName

            String m_masterName

        The name of the master plot

      - ##### m_masterPlot

            PlotData2D m_masterPlot

        The master plot

      - ##### m_maxC

            double m_maxC

      - ##### m_maxX

            double m_maxX

        Holds the min and max values of the x, y and colouring attributes over all plots

      - ##### m_maxY

            double m_maxY

      - ##### m_minC

            double m_minC

      - ##### m_minX

            double m_minX

      - ##### m_minY

            double m_minY

      - ##### m_plotCompanion

            Plot2DCompanion m_plotCompanion

        An optional "compainion" of the panel. If specified, this class will get to do its thing with our graphics context before we do any drawing. Eg. the visualize panel may need to draw polygons etc. before we draw plot axis and data points

      - ##### m_plotInstances

            Instances m_plotInstances

        The instances to be plotted

      - ##### m_plotResize

            boolean m_plotResize

        if the user resizes the window, or the attributes selected for the attributes change, then the lookup table for points needs to be recalculated

      - ##### m_plots

            ArrayList<PlotData2D> m_plots

        The plots to display

      - ##### m_sIndex

            int m_sIndex

      - ##### m_tickSize

            int m_tickSize

        Tick size

      - ##### m_XaxisEnd

            int m_XaxisEnd

      - ##### m_XaxisStart

            int m_XaxisStart

        the offsets of the axes once label metrics are calculated

      - ##### m_xIndex

            int m_xIndex

        Indexes of the attributes to go on the x and y axis and the attribute to use for colouring and the current shape for drawing

      - ##### m_YaxisEnd

            int m_YaxisEnd

      - ##### m_YaxisStart

            int m_YaxisStart

      - ##### m_yIndex

            int m_yIndex

  - ### Class weka.gui.visualize.PlotData2D

    class PlotData2D extends Object implements Serializable
    serialVersionUID:
      -3979972167982697979L

    - #### Serialized Fields

      - ##### m_alwaysDisplayPointsOfThisSize

            int m_alwaysDisplayPointsOfThisSize

        If the shape size of a point equals this size then always plot it (i.e. even if it is obscured by other points)

      - ##### m_cIndex

            int m_cIndex

        The colouring index

      - ##### m_connectPoints

            boolean[] m_connectPoints

        Additional optional information to control the drawing of lines between consecutive points. Setting an entry in the array to true indicates that the associated point should have a line connecting it to the previous point.

      - ##### m_customColour

            Color m_customColour

      - ##### m_displayAllPoints

            boolean m_displayAllPoints

        Display all points (ie. those that map to the same display coords)

      - ##### m_maxC

            double m_maxC

      - ##### m_maxX

            double m_maxX

        Holds the min and max values of the x, y and colouring attributes for this plot

      - ##### m_maxY

            double m_maxY

      - ##### m_minC

            double m_minC

      - ##### m_minX

            double m_minX

      - ##### m_minY

            double m_minY

      - ##### m_plotInstances

            Instances m_plotInstances

        The instances

      - ##### m_plotName

            String m_plotName

        The name of this plot

      - ##### m_plotNameHTML

            String m_plotNameHTML

        The name of this plot (possibly in html) suitable for using in a tool tip text.

      - ##### m_pointLookup

            double[][] m_pointLookup

        Panel coordinate cache for data points

      - ##### m_shapeSize

            int[] m_shapeSize

        Additional optional information to control the size of points. The default is shape size 2

      - ##### m_shapeType

            int[] m_shapeType

        Additional optional information to control the point shape for this data. Default is to allow automatic assigning of point shape on the basis of plot number

      - ##### m_useCustomColour

            boolean m_useCustomColour

        Custom colour for this plot

      - ##### m_xIndex

            int m_xIndex

        The x index

      - ##### m_yIndex

            int m_yIndex

        The y index

  - ### Class weka.gui.visualize.PrintableComponent.JComponentWriterFileFilter

    class JComponentWriterFileFilter extends ExtensionFileFilter implements Serializable
    serialVersionUID:
      8540426888094207515L

    - #### Serialized Fields

      - ##### m_Writer

            JComponentWriter m_Writer

        the associated writer.

  - ### Class weka.gui.visualize.PrintablePanel

    class PrintablePanel extends JPanel implements Serializable
    serialVersionUID:
      6281532227633417538L

    - #### Serialized Fields

      - ##### m_Printer

            PrintableComponent m_Printer

        the class responsible for printing

  - ### Class weka.gui.visualize.ThresholdVisualizePanel

    class ThresholdVisualizePanel extends VisualizePanel implements Serializable
    serialVersionUID:
      3070002211779443890L

    - #### Serialized Fields

      - ##### m_ROCString

            String m_ROCString

        The string to add to the Plot Border.

      - ##### m_savePanelBorderText

            String m_savePanelBorderText

        Original border text

  - ### Class weka.gui.visualize.VisualizePanel

    class VisualizePanel extends PrintablePanel implements Serializable
    serialVersionUID:
      240108358588153943L

    - #### Serialized Fields

      - ##### COMBO_SIZE

            Dimension COMBO_SIZE

        Stop the combos from growing out of control

      - ##### listener

            ActionListener listener

        An optional listener that we will inform when ComboBox selections change

      - ##### m_ArffFilter

            FileFilter m_ArffFilter

        Filter to ensure only arff files are selected

      - ##### m_attrib

            AttributePanel m_attrib

        The panel that displays the attributes , using color to represent another attribute.

      - ##### m_cancel

            JButton m_cancel

        Button for the user to remove all splits.

      - ##### m_classPanel

            ClassPanel m_classPanel

        The panel that displays the legend for the colouring attribute

      - ##### m_classSurround

            JPanel m_classSurround

        Panel that surrounds the class panel with a titled border

      - ##### m_colorList

            ArrayList<Color> m_colorList

        The list of the colors used

      - ##### m_ColourCombo

            JComboBox m_ColourCombo

        Lets the user select the attribute to use for colouring

      - ##### m_DefaultColors

            Color[] m_DefaultColors

        default colours for colouring discrete class

      - ##### m_FileChooser

            WekaFileChooser m_FileChooser

        file chooser for saving instances

      - ##### m_Jitter

            JSlider m_Jitter

        The jitter slider

      - ##### m_JitterLab

            JLabel m_JitterLab

        Label for the jitter slider

      - ##### m_legendPanel

            LegendPanel m_legendPanel

        The panel that displays legend info if there is more than one plot

      - ##### m_Log

            Logger m_Log

        the logger

      - ##### m_openBut

            JButton m_openBut

        Button for the user to open the visualized set of instances

      - ##### m_plot

            weka.gui.visualize.VisualizePanel.PlotPanel m_plot

        The panel that displays the plot

      - ##### m_plotName

            String m_plotName

        The name of the plot (not currently displayed, but can be used in the containing Frame or Panel)

      - ##### m_plotSurround

            JPanel m_plotSurround

        Panel that surrounds the plot panel with a titled border

      - ##### m_preferredColourDimension

            String m_preferredColourDimension

      - ##### m_preferredXDimension

            String m_preferredXDimension

        These hold the names of preferred columns to visualize on---if the user has defined them in the Visualize.props file

      - ##### m_preferredYDimension

            String m_preferredYDimension

      - ##### m_saveBut

            JButton m_saveBut

        Button for the user to save the visualized set of instances

      - ##### m_ShapeCombo

            JComboBox m_ShapeCombo

        Lets the user select the shape they want to create for instance selection.

      - ##### m_showAttBars

            boolean m_showAttBars

        Show the attribute bar panel

      - ##### m_showClassPanel

            boolean m_showClassPanel

        Show the class panel

      - ##### m_splitListener

            VisualizePanelListener m_splitListener

        An optional listener that we will inform when the user creates a split to seperate instances.

      - ##### m_submit

            JButton m_submit

        Button for the user to enter the splits.

      - ##### m_XCombo

            JComboBox m_XCombo

        Lets the user select the attribute for the x axis

      - ##### m_YCombo

            JComboBox m_YCombo

        Lets the user select the attribute for the y axis

  - ### Class weka.gui.visualize.VisualizePanel.PlotPanel

    class PlotPanel extends PrintablePanel implements Serializable
    serialVersionUID:
      -4823674171136494204L

    - #### Serialized Fields

      - ##### m_cIndex

            int m_cIndex

      - ##### m_createShape

            boolean m_createShape

        True if the user is currently dragging a box.

      - ##### m_newMousePos

            Dimension m_newMousePos

        contains the position of the mouse (used for rubberbanding).

      - ##### m_originalPlot

            PlotData2D m_originalPlot

        The master plot

      - ##### m_plot2D

            Plot2D m_plot2D

        The actual generic plotting panel

      - ##### m_plotInstances

            Instances m_plotInstances

        The instances from the master plot

      - ##### m_shapePoints

            ArrayList<Double> m_shapePoints

        contains the points of the shape currently being drawn.

      - ##### m_shapes

            ArrayList<ArrayList<Double>> m_shapes

        contains all the shapes that have been drawn for these attribs

      - ##### m_sIndex

            int m_sIndex

      - ##### m_xIndex

            int m_xIndex

        Indexes of the attributes to go on the x and y axis and the attribute to use for colouring and the current shape for drawing

      - ##### m_yIndex

            int m_yIndex

  - ### Class weka.gui.visualize.VisualizeUtils.VisualizeDefaults

    class VisualizeDefaults extends Defaults implements Serializable
    serialVersionUID:
      4227480313375404688L

- ## Package weka.knowledgeflow

  - ### Class weka.knowledgeflow.BaseExecutionEnvironment.BaseExecutionEnvironmentDefaults

    class BaseExecutionEnvironmentDefaults extends Defaults implements Serializable
    serialVersionUID:
      -3386792058002464330L

  - ### Class weka.knowledgeflow.Data

    class Data extends Object implements Serializable
    serialVersionUID:
      239235113781041619L

    - #### Serialized Fields

      - ##### m_connectionName

            String m_connectionName

        The connection name for this Data - determines which downstream steps will receive the data.

      - ##### m_payloadMap

            Map<String,Object> m_payloadMap

        The payload

      - ##### m_sourceStep

            Step m_sourceStep

        The source of this data

  - ### Class weka.knowledgeflow.ExecutionResult

    class ExecutionResult extends Object implements Serializable
    serialVersionUID:
      -4495164361311877942L

    - #### Serialized Fields

      - ##### m_error

            Exception m_error

        Holds any error that might have been generated

      - ##### m_executionResult

            T m_executionResult

        Holds the result payload

  - ### Class weka.knowledgeflow.KFDefaults

    class KFDefaults extends Defaults implements Serializable

  - ### Class weka.knowledgeflow.StepTask

    class StepTask extends Object implements Serializable
    serialVersionUID:
      2995081029283027784L

    - #### Serialized Fields

      - ##### m_callbackNotifier

            CallbackNotifierDelegate m_callbackNotifier

        The callback notifier delegate. Performs the actual notification back to the step

      - ##### m_log

            LogManager m_log

        The log to use

      - ##### m_mustRunSingleThreaded

            boolean m_mustRunSingleThreaded

        True if only one of these tasks can be executing at any one time in the Knowledge Flow/JVM. This has priority over isResourceIntensive() and causes the task to run on an executor service with one worker thread.

      - ##### m_resourceIntensive

            boolean m_resourceIntensive

        True if this is a high resource (cpu/memory) task

      - ##### m_result

            ExecutionResult<T> m_result

        The result of executing the task - ready to be populated by subclass's call() implementation

- ## Package weka.knowledgeflow.steps

  - ### Class weka.knowledgeflow.steps.AlterRelationName

    class AlterRelationName extends BaseStep implements Serializable
    serialVersionUID:
      5894383194664583303L

    - #### Serialized Fields

      - ##### m_hasAltered

            Set<String> m_hasAltered

        The set of source step identifiers that have had their data modified so far

      - ##### m_modType

            weka.knowledgeflow.steps.AlterRelationName.ModType m_modType

        The type of modification to make

      - ##### m_regexMatch

            String m_regexMatch

        Regex string to match

      - ##### m_regexPattern

            Pattern m_regexPattern

        For regex replacement

      - ##### m_relationNameModText

            String m_relationNameModText

        Text to modify the relation name with

      - ##### m_replaceAll

            boolean m_replaceAll

        Whether to replace all rexex matches, or just the first

  - ### Class weka.knowledgeflow.steps.Appender

    class Appender extends BaseStep implements Serializable
    serialVersionUID:
      -3003135257112845998L

    - #### Serialized Fields

      - ##### m_completed

            Map<Step,Instances> m_completed

        Used to keep track of how many upstream steps have sent us complete data sets (batch) or headers (incremental) so far.

      - ##### m_completeHeader

            Instances m_completeHeader

        Used to hold the final header in the case of incremental operation

      - ##### m_isReset

            boolean m_isReset

        True if this step has been reset

      - ##### m_streamingCountDown

            AtomicInteger m_streamingCountDown

        Gets decremented for each incoming instance stream that has finished

      - ##### m_streamingData

            Data m_streamingData

        Re-usable data object for streaming mode

      - ##### m_tempBatchFiles

            Map<Step,File> m_tempBatchFiles

        Handles on temp files used to store batches of instances in batch mode

  - ### Class weka.knowledgeflow.steps.ASEvaluator

    class ASEvaluator extends WekaAlgorithmWrapper implements Serializable
    serialVersionUID:
      -1280208826860871742L

    - #### Serialized Fields

      - ##### m_eval

            AttributeSelection m_eval

        Eval to use when performing a cross-validation and not outputting separate results for each fold

      - ##### m_evaluatorTemplate

            ASEvaluation m_evaluatorTemplate

        The evaluator (attribute or subset) being used

      - ##### m_isDoingXVal

            boolean m_isDoingXVal

        True if we are processing cross-validation folds to produce a summary over the folds (as opposed to producing separate results per fold).

      - ##### m_isRanking

            boolean m_isRanking

        Whether a ranking is being produced by the attribute selection

      - ##### m_isReset

            boolean m_isReset

        True if we've been reset

      - ##### m_numToSelectStore

            Map<Integer,Integer> m_numToSelectStore

        Holds the calculated number of attributes to select (may depend on thresholds) for each training fold

      - ##### m_searchTemplate

            ASSearch m_searchTemplate

        The search strategy being used (retrieved via an incoming "info" connection

      - ##### m_selectedAttsStore

            Map<Integer,int[]> m_selectedAttsStore

        Holds selected attribute indices corresponding to training folds

      - ##### m_setCount

            AtomicInteger m_setCount

        Keeps count of the folds processed

      - ##### m_transformerStore

            Map<Integer,AttributeTransformer> m_transformerStore

        Holds the evaluator trained per fold in the case when it is a transformer (such as PCA)

      - ##### m_treatXValFoldsSeparately

            boolean m_treatXValFoldsSeparately

        Whether to output separate evaluation results for each fold of a xval or report the cross-validation summary

      - ##### m_waitingTestData

            Map<Integer,Instances> m_waitingTestData

        Any test folds waiting to be processed (i.e. have their dimensionality reduced

  - ### Class weka.knowledgeflow.steps.ASSearchStrategy

    class ASSearchStrategy extends WekaAlgorithmWrapper implements Serializable
    serialVersionUID:
      5038697382280884975L

  - ### Class weka.knowledgeflow.steps.Associator

    class Associator extends WekaAlgorithmWrapper implements Serializable
    serialVersionUID:
      -589410455393151511L

    - #### Serialized Fields

      - ##### m_associatorTemplate

            Associator m_associatorTemplate

        Template for the associator in use

  - ### Class weka.knowledgeflow.steps.AttributeSummarizer

    class AttributeSummarizer extends BaseSimpleDataVisualizer implements Serializable
    serialVersionUID:
      2313372820072708102L

    - #### Serialized Fields

      - ##### m_additionalOptions

            String m_additionalOptions

        Additional options for the offscreen renderer

      - ##### m_height

            String m_height

        Height of offscreen plots

      - ##### m_offscreenRendererName

            String m_offscreenRendererName

        Name of the renderer to use for offscreen chart rendering

      - ##### m_width

            String m_width

        Width of offscreen plots

      - ##### m_xAxis

            String m_xAxis

        The x-axis attribute name

  - ### Class weka.knowledgeflow.steps.BaseSimpleDataVisualizer

    class BaseSimpleDataVisualizer extends BaseStep implements Serializable
    serialVersionUID:
      4955068920302509451L

    - #### Serialized Fields

      - ##### m_data

            List<Data> m_data

        The datasets seen so far

  - ### Class weka.knowledgeflow.steps.BaseStep

    class BaseStep extends Object implements Serializable
    serialVersionUID:
      -1595753549991953141L

    - #### Serialized Fields

      - ##### m_stepIsResourceIntensive

            boolean m_stepIsResourceIntensive

        True if the step is resource (cpu/memory) intensive

      - ##### m_stepName

            String m_stepName

        The name of this step component

  - ### Class weka.knowledgeflow.steps.Block

    class Block extends BaseStep implements Serializable
    serialVersionUID:
      3204082191908877620L

    - #### Serialized Fields

      - ##### m_stepToWaitFor

            String m_stepToWaitFor

        The name of the step to wait for

  - ### Class weka.knowledgeflow.steps.BoundaryPlotter

    class BoundaryPlotter extends BaseStep implements Serializable
    serialVersionUID:
      7864251468395026619L

    - #### Serialized Fields

      - ##### m_classifierTemplates

            List<Classifier> m_classifierTemplates

        Classifiers to use

      - ##### m_clustererTemplates

            List<DensityBasedClusterer> m_clustererTemplates

        Clusterers to use

      - ##### m_Colors

            List<Color> m_Colors

        Holds colors to use

      - ##### m_currentDescription

            String m_currentDescription

        The spec of the scheme being used to render the current image

      - ##### m_dataGenerator

            KDDataGenerator m_dataGenerator

        The data generator to use

      - ##### m_imageHeight

            int m_imageHeight

        Height of images to generate

      - ##### m_imageWidth

            int m_imageWidth

        Width of images to generate

      - ##### m_isReset

            boolean m_isReset

        True if we've been reset

      - ##### m_kBand

            String m_kBand

        User-specified bandwidth

      - ##### m_kernelBandwidth

            int m_kernelBandwidth

        Parsed bandwidth

      - ##### m_maxRowsInParallel

            int m_maxRowsInParallel

        Number of rows of the visualization to compute in parallel. We don't want to dominate the thread pool that is used for executing all steps and step sub-tasks in the KF (this is currently fixed at 50 threads by FlowRunner).

      - ##### m_maxX

            double m_maxX

      - ##### m_maxY

            double m_maxY

      - ##### m_minX

            double m_minX

      - ##### m_minY

            double m_minY

      - ##### m_nSamples

            String m_nSamples

        User-specified num samples

      - ##### m_numSamplesPerRegion

            int m_numSamplesPerRegion

        Parsed samples

      - ##### m_pixHeight

            double m_pixHeight

      - ##### m_pixWidth

            double m_pixWidth

      - ##### m_plotTrainingData

            boolean m_plotTrainingData

        Superimpose the training data on the plot?

      - ##### m_rangeX

            double m_rangeX

      - ##### m_rangeY

            double m_rangeY

      - ##### m_samplesBase

            int m_samplesBase

        Parsed base

      - ##### m_sBase

            String m_sBase

        User-specified base for sampling

      - ##### m_threadClassifiers

            Classifier[] m_threadClassifiers

        Copies of trained classifier to use in parallel for prediction

      - ##### m_threadClusterers

            Clusterer[] m_threadClusterers

        Copies of trained clusterer to use in parallel for prediction

      - ##### m_threadGenerators

            DataGenerator[] m_threadGenerators

        Data generator copies to use in parallel

      - ##### m_xAttName

            String m_xAttName

        X axis attribute name/index

      - ##### m_xAttribute

            int m_xAttribute

      - ##### m_yAttName

            String m_yAttName

        Y axis attribute name/index

      - ##### m_yAttribute

            int m_yAttribute

  - ### Class weka.knowledgeflow.steps.BoundaryPlotter.SchemeRowTask

    class SchemeRowTask extends StepTask<weka.knowledgeflow.steps.BoundaryPlotter.RowResult> implements Serializable
    serialVersionUID:
      -4144732293602550066L

    - #### Serialized Fields

      - ##### m_attsToWeightOn

            boolean[] m_attsToWeightOn

      - ##### m_classifier

            Classifier m_classifier

      - ##### m_clusterer

            DensityBasedClusterer m_clusterer

      - ##### m_dataGenerator

            DataGenerator m_dataGenerator

      - ##### m_dist

            double[] m_dist

      - ##### m_imageHeight

            int m_imageHeight

      - ##### m_imageWidth

            int m_imageWidth

      - ##### m_maxX

            double m_maxX

      - ##### m_maxY

            double m_maxY

      - ##### m_minX

            double m_minX

      - ##### m_minY

            double m_minY

      - ##### m_numOfSamplesPerGenerator

            int m_numOfSamplesPerGenerator

      - ##### m_numOfSamplesPerRegion

            int m_numOfSamplesPerRegion

      - ##### m_pixHeight

            double m_pixHeight

      - ##### m_pixWidth

            double m_pixWidth

      - ##### m_predInst

            Instance m_predInst

      - ##### m_random

            Random m_random

      - ##### m_rowNum

            int m_rowNum

      - ##### m_samplesBase

            double m_samplesBase

      - ##### m_trainingData

            Instances m_trainingData

      - ##### m_vals

            double[] m_vals

      - ##### m_weightingAttsValues

            double[] m_weightingAttsValues

      - ##### m_xAtt

            int m_xAtt

      - ##### m_yAtt

            int m_yAtt

  - ### Class weka.knowledgeflow.steps.ClassAssigner

    class ClassAssigner extends BaseStep implements Serializable
    serialVersionUID:
      -4269063233834866140L

    - #### Serialized Fields

      - ##### m_classAssigned

            boolean m_classAssigned

        True if the class has already been assigned

      - ##### m_classCol

            String m_classCol

        Holds user-specified class column/index

      - ##### m_classColumnS

            String m_classColumnS

        Holds resoved class column/index

      - ##### m_isInstanceStream

            boolean m_isInstanceStream

        True if processing an instance stream

      - ##### m_streamCount

            int m_streamCount

        Counter used for streams

  - ### Class weka.knowledgeflow.steps.Classifier

    class Classifier extends WekaAlgorithmWrapper implements Serializable
    serialVersionUID:
      8326706942962123155L

    - #### Serialized Fields

      - ##### m_classifierIsIncremental

            boolean m_classifierIsIncremental

        True if the classifier in use is Updateable

      - ##### m_classifierTemplate

            Classifier m_classifierTemplate

        The template for constructing concrete instances of the classifier to train

      - ##### m_incrementalData

            Data m_incrementalData

        Reusable data for incremental streaming classifiers

      - ##### m_isReset

            boolean m_isReset

        True if we've been reset

      - ##### m_loadModelFileName

            File m_loadModelFileName

        Optional file to load a pre-trained model to score with (batch, or to score and update (incremental) in the case of testSet only (batch) or instance (incremental) connections

      - ##### m_resetIncrementalClassifier

            boolean m_resetIncrementalClassifier

        True if we should resent an Updateable classifier at the start of processing for an incoming "instance" stream

      - ##### m_streaming

            boolean m_streaming

        True if we are processing streaming data

      - ##### m_trainedClassifier

            Classifier m_trainedClassifier

        Holds the trained classifier in the case of single train/test pairs or instance stream connections

      - ##### m_trainedClassifierHeader

            Instances m_trainedClassifierHeader

      - ##### m_updateIncrementalClassifier

            boolean m_updateIncrementalClassifier

        True if we should update an incremental classifier when there is a incoming "instance" stream

  - ### Class weka.knowledgeflow.steps.ClassifierPerformanceEvaluator

    class ClassifierPerformanceEvaluator extends BaseStep implements Serializable
    serialVersionUID:
      -2679292079974676672L

    - #### Serialized Fields

      - ##### m_collectDataForVisAndAUC

            boolean m_collectDataForVisAndAUC

        Whether to store test data and predictions for visualization

      - ##### m_costSensitiveEval

            boolean m_costSensitiveEval

        True to perform cost sensitive evaluation

      - ##### m_costString

            String m_costString

        The cost matrix (string form)

      - ##### m_errorPlotPointSizeProportionalToMargin

            boolean m_errorPlotPointSizeProportionalToMargin

        True if plot point sizes are to be rendered proportional to the size of the prediction margin

      - ##### m_isReset

            boolean m_isReset

        True if the step has been reset

      - ##### m_matrix

            CostMatrix m_matrix

        The cost matrix

      - ##### m_maxSetNum

            int m_maxSetNum

        The maximum set number in the batch of sets being processed

      - ##### m_metricsList

            List<String> m_metricsList

        Holds a list of metric names

      - ##### m_outputConfusionMatrix

            boolean m_outputConfusionMatrix

        True to output confusion matrix

      - ##### m_outputEntropyMetrics

            boolean m_outputEntropyMetrics

        True to output entropy-based metrics

      - ##### m_outputPerClassStats

            boolean m_outputPerClassStats

        True to output of per class stats

      - ##### m_selectedEvalMetrics

            String m_selectedEvalMetrics

        Evaluation metrics to output

      - ##### m_setsToGo

            AtomicInteger m_setsToGo

        For counting down the sets left to process

      - ##### m_taskCount

            AtomicInteger m_taskCount

  - ### Class weka.knowledgeflow.steps.ClassifierPerformanceEvaluator.AggregateableClassifierErrorsPlotInstances

    class AggregateableClassifierErrorsPlotInstances extends ClassifierErrorsPlotInstances implements Serializable
    serialVersionUID:
      2012744784036684168L

  - ### Class weka.knowledgeflow.steps.ClassifierPerformanceEvaluator.EvaluationTask

    class EvaluationTask extends StepTask<Object[]> implements Serializable
    serialVersionUID:
      -686972773536075889L

    - #### Serialized Fields

      - ##### m_classifier

            Classifier m_classifier

      - ##### m_classifierDesc

            String m_classifierDesc

      - ##### m_cMatrix

            CostMatrix m_cMatrix

      - ##### m_collectPreds

            boolean m_collectPreds

      - ##### m_errPlotPtSizePropToMarg

            boolean m_errPlotPtSizePropToMarg

      - ##### m_evalLabel

            String m_evalLabel

      - ##### m_metricsList

            List<String> m_metricsList

      - ##### m_setNum

            int m_setNum

      - ##### m_testData

            Instances m_testData

      - ##### m_trainData

            Instances m_trainData

  - ### Class weka.knowledgeflow.steps.ClassValuePicker

    class ClassValuePicker extends BaseStep implements Serializable
    serialVersionUID:
      8558445535347028472L

    - #### Serialized Fields

      - ##### m_classIsNominal

            boolean m_classIsNominal

        True if the class is set and is nominal

      - ##### m_classIsSet

            boolean m_classIsSet

        True if the class is set in the incoming data

      - ##### m_classValue

            String m_classValue

        Class label after environment variables have been resolved

      - ##### m_classValueS

            String m_classValueS

        User specified class label, label index or special identifier (e.g "first"/"last")

  - ### Class weka.knowledgeflow.steps.Clusterer

    class Clusterer extends WekaAlgorithmWrapper implements Serializable
    serialVersionUID:
      3275754421525338036L

    - #### Serialized Fields

      - ##### m_clustererTemplate

            Clusterer m_clustererTemplate

        The template for constructing concrete instances of the clusterer to train

      - ##### m_incrementalData

            Data m_incrementalData

        Re-usable Data object for incrementalClusterer output

      - ##### m_isReset

            boolean m_isReset

        True if the step has just been reset

      - ##### m_loadModelFileName

            File m_loadModelFileName

        Optional file to load a pre-trained model to score with (batch, or to score and update (incremental) in the case of testSet only (batch) or instance (incremental) connections

      - ##### m_streaming

            boolean m_streaming

        True if there is a single incoming "instance" connection

      - ##### m_trainedClusterer

            Clusterer m_trainedClusterer

        Holds a trained/loaded clusterer

      - ##### m_trainedClustererHeader

            Instances m_trainedClustererHeader

        Header used to train the clusterer

  - ### Class weka.knowledgeflow.steps.ClustererPerformanceEvaluator

    class ClustererPerformanceEvaluator extends BaseStep implements Serializable
    serialVersionUID:
      -6337375482954345717L

  - ### Class weka.knowledgeflow.steps.CostBenefitAnalysis

    class CostBenefitAnalysis extends BaseSimpleDataVisualizer implements Serializable
    serialVersionUID:
      7756281775575854085L

  - ### Class weka.knowledgeflow.steps.CrossValidationFoldMaker

    class CrossValidationFoldMaker extends BaseStep implements Serializable
    serialVersionUID:
      6090713408437825355L

    - #### Serialized Fields

      - ##### m_numFolds

            int m_numFolds

        Resolved number of folds

      - ##### m_numFoldsS

            String m_numFoldsS

        User-specified number of folds

      - ##### m_preserveOrder

            boolean m_preserveOrder

        True to preserve order of the instances rather than randomly shuffling

      - ##### m_seed

            long m_seed

        Resolved random seed

      - ##### m_seedS

            String m_seedS

        User-specified random seed

  - ### Class weka.knowledgeflow.steps.DataGenerator

    class DataGenerator extends WekaAlgorithmWrapper implements Serializable
    serialVersionUID:
      -7716707145987484527L

    - #### Serialized Fields

      - ##### m_flowThroughput

            StreamThroughput m_flowThroughput

        overall flow throughput when streaming

      - ##### m_incrementalData

            Data m_incrementalData

        reusable data object for streaming

  - ### Class weka.knowledgeflow.steps.DataGrid

    class DataGrid extends BaseStep implements Serializable
    serialVersionUID:
      1318159328875458847L

    - #### Serialized Fields

      - ##### m_data

            String m_data

        The instances to output (as a string)

      - ##### m_flowThroughput

            StreamThroughput m_flowThroughput

        For overall stream throughput measuring

      - ##### m_incrementalData

            Data m_incrementalData

        Reusable data object for streaming output

  - ### Class weka.knowledgeflow.steps.DataVisualizer

    class DataVisualizer extends BaseStep implements Serializable
    serialVersionUID:
      -8013077913672918384L

    - #### Serialized Fields

      - ##### m_additionalOptions

            String m_additionalOptions

        Additional options for the offscreen renderer

      - ##### m_height

            String m_height

        Height of offscreen plots

      - ##### m_offscreenRendererName

            String m_offscreenRendererName

        Name of the renderer to use for offscreen chart rendering

      - ##### m_plots

            List<PlotData2D> m_plots

        Current set of plots. First element is the master plot

      - ##### m_width

            String m_width

        Width of offscreen plots

      - ##### m_xAxis

            String m_xAxis

        The name of the attribute to use for the x-axis of offscreen plots. If left empty, False Positive Rate is used for threshold curves

      - ##### m_yAxis

            String m_yAxis

        The name of the attribute to use for the y-axis of offscreen plots. If left empty, True Positive Rate is used for threshold curves

  - ### Class weka.knowledgeflow.steps.Dummy

    class Dummy extends BaseStep implements Serializable
    serialVersionUID:
      -5822675617001689385L

  - ### Class weka.knowledgeflow.steps.ExecuteProcess

    class ExecuteProcess extends BaseStep implements Serializable
    serialVersionUID:
      -9153714279540182885L

    - #### Serialized Fields

      - ##### m_argsFieldIndex

            int m_argsFieldIndex

        Resolved attribute index of dynamic arguments

      - ##### m_cmdFieldIndex

            int m_cmdFieldIndex

        Resolved attribute index of dynamic command

      - ##### m_fieldArgs

            String m_fieldArgs

        Name of attribute that will hold optional arguments for dynamic command

      - ##### m_fieldCmd

            String m_fieldCmd

        Name of attribute that will hold dynamic command to be executed

      - ##### m_fieldWorkingDir

            String m_fieldWorkingDir

        Name of attribute that will hold optional working directory for dynamic command

      - ##### m_instanceOutHeader

            Instances m_instanceOutHeader

        Structure of output for outgoing instance connections

      - ##### m_raiseAnExceptionOnCommandFailure

            boolean m_raiseAnExceptionOnCommandFailure

        Whether to raise an exception when a command fails completely (i.e. doesn't exist or something) vs the case of a non-zero exit status. If not raising an exception, then output indicating failure (with exist status = 1 in the case of instance connections) will be generated

      - ##### m_runningProcess

            Process m_runningProcess

        The process that is used to execute the user's command(s)

      - ##### m_staticArgs

            String m_staticArgs

        Arguments (if necessary) for single static command

      - ##### m_staticExecCmd

            String m_staticExecCmd

        Single static command (may use env vars)

      - ##### m_staticWorkingDir

            String m_staticWorkingDir

        Optional working directory for single static command

      - ##### m_stdErrBuffer

            StringBuffer m_stdErrBuffer

        Std err from process

      - ##### m_stdOutbuffer

            StringBuffer m_stdOutbuffer

        Std out from process

      - ##### m_structureCheckComplete

            boolean m_structureCheckComplete

        True if the structure has been checked

      - ##### m_useDynamic

            boolean m_useDynamic

        True to execute commands specified in incoming instance fields

      - ##### m_workingDirFieldIndex

            int m_workingDirFieldIndex

        Resolved attribute index of dynamic working directory

  - ### Class weka.knowledgeflow.steps.Filter

    class Filter extends WekaAlgorithmWrapper implements Serializable
    serialVersionUID:
      6857031910153224479L

    - #### Serialized Fields

      - ##### m_filterMap

            Map<Integer,Filter> m_filterMap

        Map of filters that have processed the first batch

      - ##### m_filterTemplate

            Filter m_filterTemplate

        Template filter

      - ##### m_incrementalData

            Data m_incrementalData

        Data object to reuse when processing incrementally

      - ##### m_isReset

            boolean m_isReset

        True if we've been reset

      - ##### m_setCount

            AtomicInteger m_setCount

        Keeps track of the number of train/test batches processed

      - ##### m_streaming

            boolean m_streaming

        True if we're streaming

      - ##### m_streamingFilter

            Filter m_streamingFilter

        Used when processing streaming data

      - ##### m_stringAttsPresent

            boolean m_stringAttsPresent

        True if string attributes are present in streaming case

      - ##### m_waitingTestData

            Map<Integer,Instances> m_waitingTestData

        Map of waiting test sets when batch filtering

  - ### Class weka.knowledgeflow.steps.FlowByExpression

    class FlowByExpression extends BaseStep implements Serializable
    serialVersionUID:
      7006511778677802572L

    - #### Serialized Fields

      - ##### m_batchCount

            AtomicInteger m_batchCount

        Keep track of how many incoming batches we've seen

      - ##### m_customNameOfFalseStep

            String m_customNameOfFalseStep

        Name of the step to receive instances that evaluate to false via the expression

      - ##### m_customNameOfTrueStep

            String m_customNameOfTrueStep

        Name of the step to receive instances that evaluate to true via the expression

      - ##### m_expressionString

            String m_expressionString

        The expression tree to use in internal textual format

      - ##### m_incomingStructure

            Instances m_incomingStructure

        Incoming structure

      - ##### m_isReset

            boolean m_isReset

      - ##### m_root

            FlowByExpression.ExpressionNode m_root

        The root of the expression tree

      - ##### m_streamingData

            Data m_streamingData

        Re-usable data object for streaming

      - ##### m_validFalseStep

            boolean m_validFalseStep

        True if the "false" step is valid (i.e. exists in the flow)

      - ##### m_validTrueStep

            boolean m_validTrueStep

        True if the "true" step is valid (i.e. exists in the flow)

  - ### Class weka.knowledgeflow.steps.FlowByExpression.BracketNode

    class BracketNode extends FlowByExpression.ExpressionNode implements Serializable
    serialVersionUID:
      8732159083173001115L

    - #### Serialized Fields

      - ##### m_children

            List<FlowByExpression.ExpressionNode> m_children

  - ### Class weka.knowledgeflow.steps.FlowByExpression.ExpressionClause

    class ExpressionClause extends FlowByExpression.ExpressionNode implements Serializable
    serialVersionUID:
      2754006654981248325L

    - #### Serialized Fields

      - ##### m_lhsAttIndex

            int m_lhsAttIndex

        The index of the lhs attribute

      - ##### m_lhsAttributeName

            String m_lhsAttributeName

        The name of the lhs attribute

      - ##### m_numericOperand

            double m_numericOperand

        The rhs operand (if constant and is a number )

      - ##### m_operator

            FlowByExpression.ExpressionClause.ExpressionType m_operator

        The operator for this expression

      - ##### m_regexPattern

            Pattern m_regexPattern

        the compiled regex pattern (if the operator is REGEX)

      - ##### m_resolvedLhsName

            String m_resolvedLhsName

        The name of the lhs attribute after resolving variables

      - ##### m_resolvedRhsOperand

            String m_resolvedRhsOperand

        The rhs operand after resolving variables

      - ##### m_rhsAttIndex

            int m_rhsAttIndex

        index of the rhs if it is an attribute

      - ##### m_rhsIsAttribute

            boolean m_rhsIsAttribute

        True if the rhs operand is an attribute

      - ##### m_rhsOperand

            String m_rhsOperand

        The rhs operand (constant value or attribute name)

  - ### Class weka.knowledgeflow.steps.FlowByExpression.ExpressionNode

    class ExpressionNode extends Object implements Serializable
    serialVersionUID:
      -8427857202322768762L

    - #### Serialized Fields

      - ##### m_isAnOr

            boolean m_isAnOr

        boolean operator for combining with result so far

      - ##### m_isNegated

            boolean m_isNegated

        is this node negated?

      - ##### m_showAndOr

            boolean m_showAndOr

        Whether to show the combination operator in the textual representation

  - ### Class weka.knowledgeflow.steps.GetDataFromResult

    class GetDataFromResult extends BaseStep implements Serializable
    serialVersionUID:
      7447845310997458636L

  - ### Class weka.knowledgeflow.steps.GraphViewer

    class GraphViewer extends BaseSimpleDataVisualizer implements Serializable
    serialVersionUID:
      -3256888744740965144L

  - ### Class weka.knowledgeflow.steps.ImageSaver

    class ImageSaver extends BaseStep implements Serializable
    serialVersionUID:
      -8766164679635957891L

    - #### Serialized Fields

      - ##### m_defaultFile

            String m_defaultFile

        Default location to write to, in case a file has not been explicitly set

      - ##### m_defaultFormat

            weka.knowledgeflow.steps.ImageSaver.ImageFormat m_defaultFormat

        Default format to use - read from the settings for this step, and used in the case when the user has selected/left DEFAULT as the format type in the step's options. Must not be set to the type DEFAULT of course :-)

      - ##### m_file

            File m_file

        The file to save to

      - ##### m_format

            weka.knowledgeflow.steps.ImageSaver.ImageFormat m_format

        Format to save to. If set to DEFAULT, then the default format the user has set in the settings for this step is used.

      - ##### m_imageCounter

            int m_imageCounter

        Gets incremented by 1 for each image received during execution. Can be used (via the image_count variable) to ensure that each image gets saved to a different file when there are multiple images expected during execution.

  - ### Class weka.knowledgeflow.steps.ImageSaver.ImageSaverDefaults

    class ImageSaverDefaults extends Defaults implements Serializable
    serialVersionUID:
      -2739579935119189195L

  - ### Class weka.knowledgeflow.steps.ImageViewer

    class ImageViewer extends BaseStep implements Serializable
    serialVersionUID:
      -4055716444227948343L

    - #### Serialized Fields

      - ##### m_images

            Map<String,BufferedImage> m_images

        Holds the received images

  - ### Class weka.knowledgeflow.steps.IncrementalClassifierEvaluator

    class IncrementalClassifierEvaluator extends BaseStep implements Serializable
    serialVersionUID:
      -5951569492213633100L

    - #### Serialized Fields

      - ##### m_chartData

            Data m_chartData

        Re-usable chart data

      - ##### m_classifierName

            String m_classifierName

        Holds the name of the classifier being used

      - ##### m_dataLegend

            List<String> m_dataLegend

        Legend information

      - ##### m_dataPoint

            double[] m_dataPoint

        Actual data point values

      - ##### m_eval

            Evaluation m_eval

        Main eval object

      - ##### m_instanceCount

            int m_instanceCount

        Count of instances seen

      - ##### m_max

            double m_max

      - ##### m_min

            double m_min

      - ##### m_outputInfoRetrievalStats

            boolean m_outputInfoRetrievalStats

      - ##### m_reset

            boolean m_reset

        True if rest

      - ##### m_statusFrequency

            int m_statusFrequency

        how often (in milliseconds) to report throughput to the log

      - ##### m_window

            LinkedList<Instance> m_window

        Window instances

      - ##### m_windowedPreds

            LinkedList<double[]> m_windowedPreds

        Window predictions

      - ##### m_windowEval

            Evaluation m_windowEval

        Evaluation object for window

      - ##### m_windowSize

            int m_windowSize

        window size for computing performance metrics - 0 means no window, i.e don't "forget" performance on any instances

  - ### Class weka.knowledgeflow.steps.InstanceStreamToBatchMaker

    class InstanceStreamToBatchMaker extends BaseStep implements Serializable
    serialVersionUID:
      5461324282251111320L

    - #### Serialized Fields

      - ##### m_hasStringAtts

            boolean m_hasStringAtts

        True if the incoming data contains string attributes

      - ##### m_isReset

            boolean m_isReset

        True if we've been reset

      - ##### m_structure

            Instances m_structure

        The structure of the incoming instances

  - ### Class weka.knowledgeflow.steps.Job

    class Job extends BaseStep implements Serializable
    serialVersionUID:
      -8684065684979500325L

    - #### Serialized Fields

      - ##### m_flowToRun

            File m_flowToRun

      - ##### m_logLevel

            LoggingLevel m_logLevel

  - ### Class weka.knowledgeflow.steps.Join

    class Join extends BaseStep implements Serializable
    serialVersionUID:
      -8248954818247532014L

    - #### Serialized Fields

      - ##### m_firstInput

            StepManager m_firstInput

        First source of data

      - ##### m_firstInputConnectionType

            String m_firstInputConnectionType

        Connection type of the first input

      - ##### m_firstIsWaiting

            boolean m_firstIsWaiting

        True if the first input stream is waiting due to a full buffer (incremental mode only)

      - ##### m_keyIndexesOne

            int[] m_keyIndexesOne

        Indexes of the key fields for the first input

      - ##### m_keyIndexesTwo

            int[] m_keyIndexesTwo

        Indexes of the key fields for the second input

      - ##### m_keySpec

            String m_keySpec

        Holds the internal representation of the key specification

      - ##### m_runningIncrementally

            boolean m_runningIncrementally

        True if the step is running incrementally

      - ##### m_secondInput

            StepManager m_secondInput

        Second source of data

      - ##### m_secondInputConnectionType

            String m_secondInputConnectionType

        Connection type of the second input

      - ##### m_secondIsWaiting

            boolean m_secondIsWaiting

        True if the second input stream is waiting due to a full buffer (incremental mode only)

      - ##### m_streamingData

            Data m_streamingData

        Reusable data object for streaming output

      - ##### m_stringAttIndexesOne

            Map<String,Integer> m_stringAttIndexesOne

        Holds indexes of string attributes, keyed by attribute name

      - ##### m_stringAttIndexesTwo

            Map<String,Integer> m_stringAttIndexesTwo

        Holds indexes of string attributes, keyed by attribute name

      - ##### m_stringAttsPresent

            boolean m_stringAttsPresent

        True if string attributes are present in the incoming data

  - ### Class weka.knowledgeflow.steps.Loader

    class Loader extends WekaAlgorithmWrapper implements Serializable
    serialVersionUID:
      -788869066035779154L

    - #### Serialized Fields

      - ##### m_flowThroughput

            StreamThroughput m_flowThroughput

        For measuring the overall flow throughput

      - ##### m_globalInfo

            String m_globalInfo

        Global info for the wrapped loader (if it exists).

      - ##### m_instanceData

            Data m_instanceData

        Reusable data container

      - ##### m_instanceGeneration

            boolean m_instanceGeneration

        True if we're going to be streaming instance objects

      - ##### m_noOutputs

            boolean m_noOutputs

        True if there are no outgoing connections

  - ### Class weka.knowledgeflow.steps.MakeResourceIntensive

    class MakeResourceIntensive extends BaseStep implements Serializable
    serialVersionUID:
      -5670771681991035130L

    - #### Serialized Fields

      - ##### m_setAsResourceIntensive

            boolean m_setAsResourceIntensive

        True if downstream steps are to be made resource intensive

  - ### Class weka.knowledgeflow.steps.MemoryBasedDataSource

    class MemoryBasedDataSource extends BaseStep implements Serializable
    serialVersionUID:
      -1901014330145130275L

    - #### Serialized Fields

      - ##### m_instances

            Instances m_instances

        The data that will be output from this step

  - ### Class weka.knowledgeflow.steps.ModelPerformanceChart

    class ModelPerformanceChart extends BaseStep implements Serializable
    serialVersionUID:
      6166590810777938147L

    - #### Serialized Fields

      - ##### m_additionalOptions

            String m_additionalOptions

        Additional options for the offscreen renderer

      - ##### m_dataIsThresholdData

            boolean m_dataIsThresholdData

        True if the collected plots contain threshold data

      - ##### m_height

            String m_height

        Height of offscreen plots

      - ##### m_offscreenRendererName

            String m_offscreenRendererName

        Name of the renderer to use for offscreen chart rendering

      - ##### m_plots

            List<PlotData2D> m_plots

        Current set of plots. First element is the master plot

      - ##### m_width

            String m_width

        Width of offscreen plots

      - ##### m_xAxis

            String m_xAxis

        The name of the attribute to use for the x-axis of offscreen plots. If left empty, False Positive Rate is used for threshold curves

      - ##### m_yAxis

            String m_yAxis

        The name of the attribute to use for the y-axis of offscreen plots. If left empty, True Positive Rate is used for threshold curves

  - ### Class weka.knowledgeflow.steps.Note

    class Note extends BaseStep implements Serializable

    - #### Serialized Fields

      - ##### m_noteText

            String m_noteText

        The text of the note

  - ### Class weka.knowledgeflow.steps.PairedDataHelper

    class PairedDataHelper extends Object implements Serializable
    serialVersionUID:
      -7813465607881227514L

    - #### Serialized Fields

      - ##### m_namedIndexedStore

            Map<String,Map<Integer,Object>> m_namedIndexedStore

        Storage of arbitrary indexed results computed during execution of PairedProcessor.processPrimary()

      - ##### m_primaryConType

            String m_primaryConType

        The type of connection to route to PairedProcessor.processPrimary()

      - ##### m_primaryResultMap

            Map<Integer,P> m_primaryResultMap

        Storage of the indexed primary result

      - ##### m_secondaryConType

            String m_secondaryConType

        The type of connection to route to PairedProcessor.processSecondary()

      - ##### m_secondaryDataMap

            Map<Integer,Data> m_secondaryDataMap

        Holds the secondary data objects, if they arrive before the corresponding primary has been computed

  - ### Class weka.knowledgeflow.steps.PredictionAppender

    class PredictionAppender extends BaseStep implements Serializable
    serialVersionUID:
      3558618759400903936L

    - #### Serialized Fields

      - ##### m_appendProbabilities

            boolean m_appendProbabilities

        True if probabilities are to be appended

      - ##### m_instanceData

            Data m_instanceData

        Re-usable Data object for streaming output

      - ##### m_streamingOutputStructure

            Instances m_streamingOutputStructure

        Holds structure of streaming output

      - ##### m_stringAttIndexes

            List<Integer> m_stringAttIndexes

        Keep track of indexes of string attributes in the streaming case

  - ### Class weka.knowledgeflow.steps.Saver

    class Saver extends WekaAlgorithmWrapper implements Serializable
    serialVersionUID:
      6831606284211403465L

    - #### Serialized Fields

      - ##### m_isDBSaver

            boolean m_isDBSaver

        True if the saver is a DatabaseSaver

      - ##### m_relationNameForFilename

            boolean m_relationNameForFilename

        For file-based savers - if true (default), relation name is used as the primary part of the filename. If false, then the prefix is used as the filename. Useful for preventing filenames from getting too long when there are many filters in a flow.

      - ##### m_saver

            Saver m_saver

        The actual saver instance to use

      - ##### m_structure

            Instances m_structure

        Holds the structure

  - ### Class weka.knowledgeflow.steps.ScatterPlotMatrix

    class ScatterPlotMatrix extends BaseSimpleDataVisualizer implements Serializable
    serialVersionUID:
      -2033576643553187310L

  - ### Class weka.knowledgeflow.steps.SendToPerspective

    class SendToPerspective extends BaseStep implements Serializable
    serialVersionUID:
      7322550048407408819L

    - #### Serialized Fields

      - ##### m_perspectiveName

            String m_perspectiveName

  - ### Class weka.knowledgeflow.steps.SerializedModelSaver

    class SerializedModelSaver extends BaseStep implements Serializable
    serialVersionUID:
      -8343162241983197708L

    - #### Serialized Fields

      - ##### m_counter

            int m_counter

        Counter for use when processing incremental classifier connections

      - ##### m_directory

            File m_directory

        The directory to hold the saved model(s)

      - ##### m_filenamePrefix

            String m_filenamePrefix

        The prefix for the file name (model + training set info will be appended)

      - ##### m_includeRelationName

            boolean m_includeRelationName

        Whether to include the relation name of the data in the file name for the model

      - ##### m_incrementalHeader

            Instances m_incrementalHeader

        Stores the header of data used to build an incremental model

      - ##### m_incrementalSaveSchedule

            int m_incrementalSaveSchedule

        How often to save an incremental classifier (<= 0 means only at the end of the stream)

  - ### Class weka.knowledgeflow.steps.SetPropertiesFromEnvironment

    class SetPropertiesFromEnvironment extends BaseStep implements Serializable
    serialVersionUID:
      -8316084792512232973L

  - ### Class weka.knowledgeflow.steps.SetVariables

    class SetVariables extends BaseStep implements Serializable
    serialVersionUID:
      8042350408846800738L

    - #### Serialized Fields

      - ##### m_dynamicInternalRep

            String m_dynamicInternalRep

        Holds dynamic variables in internal representation

      - ##### m_internalRep

            String m_internalRep

        Holds static variables in internal representation

      - ##### m_raiseErrorWhenValueMissing

            boolean m_raiseErrorWhenValueMissing

        True if an exception should be raised when an attribute value being used to set a variable is missing, instead of using a default value

      - ##### m_structureCheckComplete

            boolean m_structureCheckComplete

        True if the structure has been checked

      - ##### m_structureOK

            boolean m_structureOK

        OK if there is at least one specified attribute in the incoming instance structure

      - ##### m_varsToSet

            Map<String,String> m_varsToSet

        Map of variables to set with fixed values

      - ##### m_varsToSetFromIncomingInstances

            Map<String,List<String>> m_varsToSetFromIncomingInstances

        Map of variables to set based on the values of attributes in incoming instances

  - ### Class weka.knowledgeflow.steps.Sorter

    class Sorter extends BaseStep implements Serializable
    serialVersionUID:
      3373283983192467264L

    - #### Serialized Fields

      - ##### m_bufferSize

            String m_bufferSize

        Size of the in-memory buffer

      - ##### m_bufferSizeI

            int m_bufferSizeI

        Size of the in-memory buffer after resolving any environment vars

      - ##### m_connectedFormat

            Instances m_connectedFormat

        format of instances for current incoming connection (if any)

      - ##### m_isReset

            boolean m_isReset

        True if we've been reset

      - ##### m_sortDetails

            String m_sortDetails

        Holds the internal textual description of the sort definitions

      - ##### m_streaming

            boolean m_streaming

        True if processing streaming data

      - ##### m_streamingData

            Data m_streamingData

        To (re)use when streaming

      - ##### m_stringAttIndexes

            Map<String,Integer> m_stringAttIndexes

        Holds indexes of string attributes, keyed by attribute name

      - ##### m_tempDirectory

            File m_tempDirectory

        The directory to hold the temp files - if not set the system tmp directory is used

  - ### Class weka.knowledgeflow.steps.Sorter.InstanceHolder

    class InstanceHolder extends Object implements Serializable
    serialVersionUID:
      -3985730394250172995L

    - #### Serialized Fields

      - ##### m_fileNumber

            int m_fileNumber

        index into the list of files on disk

      - ##### m_instance

            Instance m_instance

        The instance

      - ##### m_stringVals

            Map<String,String> m_stringVals

        for incremental operation, if string attributes are present then we need to store them with each instance - since incremental streaming in the knowledge flow only maintains one string value in memory (and hence in the header) at any one time

  - ### Class weka.knowledgeflow.steps.StorePropertiesInEnvironment

    class StorePropertiesInEnvironment extends BaseStep implements Serializable
    serialVersionUID:
      -1526289154505863542L

    - #### Serialized Fields

      - ##### m_internalRep

            String m_internalRep

        Internal string-based representation of property configs

      - ##### m_propsToSetFromIncomingInstances

            Map<String,List<String>> m_propsToSetFromIncomingInstances

        Map of properties to set based on the values of attributes in incoming instances. Keyed by attribute name/index. List contains target step name, property path (can be empty string to indicate a command line spec for a complete base-scheme config), default property value. If an incoming attribute value is missing, and no default property value is available, an exception will be generated.

      - ##### m_raiseErrorWhenValueMissing

            boolean m_raiseErrorWhenValueMissing

      - ##### m_structureCheckComplete

            boolean m_structureCheckComplete

        True if the structure has been checked

      - ##### m_structureOK

            boolean m_structureOK

        OK if there is at least one specified attribute in the incoming instance structure

  - ### Class weka.knowledgeflow.steps.StripChart

    class StripChart extends BaseStep implements Serializable
    serialVersionUID:
      -2569383350174947630L

    - #### Serialized Fields

      - ##### m_instanceWidth

            int m_instanceWidth

        Holds the number of attribute values (10 max) to plot if processing an incoming instance stream

      - ##### m_plotListeners

            List<StripChart.PlotNotificationListener> m_plotListeners

        Parties interested in knowing about updates

      - ##### m_refreshFrequency

            int m_refreshFrequency

        Plot every m_refreshFrequency'th point

      - ##### m_reset

            boolean m_reset

        True if we've been reset

      - ##### m_userRefreshWidth

            int m_userRefreshWidth

      - ##### m_xValFreq

            int m_xValFreq

        Frequency for plotting x values

  - ### Class weka.knowledgeflow.steps.SubstringLabeler

    class SubstringLabeler extends BaseStep implements Serializable
    serialVersionUID:
      1409175779108600014L

    - #### Serialized Fields

      - ##### m_addFilter

            Add m_addFilter

        Add filter for adding the new attribute

      - ##### m_attName

            String m_attName

        Name of the new attribute

      - ##### m_consumeNonMatchingInstances

            boolean m_consumeNonMatchingInstances

        For multi-valued labeled rules, whether or not to consume non-matching instances or output them with missing value for the match attribute.

      - ##### m_isReset

            boolean m_isReset

        Step has been reset - i.e. start of processing?

      - ##### m_matchDetails

            String m_matchDetails

        Internally encoded list of match rules

      - ##### m_nominalBinary

            boolean m_nominalBinary

        Whether to make the binary match/non-match attribute a nominal (rather than numeric) binary attribute.

      - ##### m_streaming

            boolean m_streaming

        Streaming instances?

      - ##### m_streamingData

            Data m_streamingData

        Reusable data object for output

  - ### Class weka.knowledgeflow.steps.SubstringReplacer

    class SubstringReplacer extends BaseStep implements Serializable
    serialVersionUID:
      -8786642000811852824L

    - #### Serialized Fields

      - ##### m_isReset

            boolean m_isReset

        Step has been reset - i.e. start of processing

      - ##### m_matchReplaceDetails

            String m_matchReplaceDetails

        Internally encoded list of match-replace rules

      - ##### m_streamingData

            Data m_streamingData

        Reusable data object for output

  - ### Class weka.knowledgeflow.steps.TestSetMaker

    class TestSetMaker extends BaseStep implements Serializable
    serialVersionUID:
      6384920860783839811L

  - ### Class weka.knowledgeflow.steps.TextSaver

    class TextSaver extends BaseStep implements Serializable
    serialVersionUID:
      -1434752243260858338L

    - #### Serialized Fields

      - ##### m_append

            boolean m_append

        Whether to append to the file or not

      - ##### m_defaultFile

            String m_defaultFile

        Default location to write to, in case a file has not been explicitly set

      - ##### m_file

            File m_file

        The file to save to

      - ##### m_writeTitleString

            boolean m_writeTitleString

        Whether to write the title string for each textual result too

  - ### Class weka.knowledgeflow.steps.TextSaver.TextSaverDefaults

    class TextSaverDefaults extends Defaults implements Serializable
    serialVersionUID:
      -2739579935119189195L

  - ### Class weka.knowledgeflow.steps.TextViewer

    class TextViewer extends BaseStep implements Serializable
    serialVersionUID:
      8602416209256135064L

    - #### Serialized Fields

      - ##### m_results

            Map<String,String> m_results

        Holds textual results

  - ### Class weka.knowledgeflow.steps.TrainingSetMaker

    class TrainingSetMaker extends BaseStep implements Serializable
    serialVersionUID:
      1082946912813721183L

  - ### Class weka.knowledgeflow.steps.TrainTestSplitMaker

    class TrainTestSplitMaker extends BaseStep implements Serializable
    serialVersionUID:
      7685026723199727685L

    - #### Serialized Fields

      - ##### m_preserveOrder

            boolean m_preserveOrder

        Whether to preserve the order of the data before making the split, rather than randomly shuffling

      - ##### m_seed

            long m_seed

        Resolved seed

      - ##### m_seedS

            String m_seedS

        Default seed for the random number generator

      - ##### m_trainPercentage

            double m_trainPercentage

        Resolved percentage

      - ##### m_trainPercentageS

            String m_trainPercentageS

        Default split percentage

  - ### Class weka.knowledgeflow.steps.WekaAlgorithmWrapper

    class WekaAlgorithmWrapper extends BaseStep implements Serializable
    serialVersionUID:
      -1013404060247467085L

    - #### Serialized Fields

      - ##### m_defaultIconPath

            String m_defaultIconPath

        Icon path to the default icon for the type of wrapped algorithm - e.g. Classifier, Loader etc.

      - ##### m_defaultPackageIconPath

            String m_defaultPackageIconPath

        Icon path to the default icon at the package level - e.g. weka.classifiers.rules

      - ##### m_iconPath

            String m_iconPath

        Icon path to the specific icon for the wrapped algorithim

      - ##### m_wrappedAlgorithm

            Object m_wrappedAlgorithm

        The wrapped algorithm

  - ### Class weka.knowledgeflow.steps.WriteDataToResult

    class WriteDataToResult extends BaseStep implements Serializable
    serialVersionUID:
      -1932252461151862615L

  - ### Class weka.knowledgeflow.steps.WriteWekaLog

    class WriteWekaLog extends BaseStep implements Serializable
    serialVersionUID:
      -2306717547200779711L

    - #### Serialized Fields

      - ##### m_incrCount

            int m_incrCount

        Count of how many incremental data points have been seen so far

      - ##### m_incrementalWriteFrequency

            String m_incrementalWriteFrequency

        How often to write incremental data to the log

      - ##### m_incrFreq

            int m_incrFreq

        Resolved frequency

      - ##### m_inputIsIncremental

            boolean m_inputIsIncremental

        True if the input is incremental

      - ##### m_isReset

            boolean m_isReset

        True if the step has been reset

      - ##### m_logLevel

            LoggingLevel m_logLevel

        Level to log at