# Package weka.attributeSelection

package weka.attributeSelection

- Related Packages
  Package
  Description
  weka
- Class
  Description
  ASEvaluation
  Abstract attribute selection evaluation class
  ASSearch
  Abstract attribute selection search class.
  AttributeEvaluator
  Interface for classes that evaluate attributes individually.
  AttributeSelection
  Attribute selection class.
  AttributeSetEvaluator
  Abstract attribute set evaluator.
  AttributeTransformer
  Abstract attribute transformer.
  BestFirst
  BestFirst:
  Searches the space of attribute subsets by greedy hillclimbing augmented with a backtracking facility.
  CfsSubsetEval
  CfsSubsetEval :
  Evaluates the worth of a subset of attributes by considering the individual predictive ability of each feature along with the degree of redundancy between them.
  Subsets of features that are highly correlated with the class while having low intercorrelation are preferred.
  For more information see:
  M.
  CheckAttributeSelection
  Class for examining the capabilities and finding problems with attribute selection schemes.
  ClassifierAttributeEval
  ClassifierAttributeEval :
  Evaluates the worth of an attribute by using a user-specified classifier.
  ClassifierSubsetEval
  Classifier subset evaluator:
  Evaluates attribute subsets on training data or a separate hold out testing set.
  CorrelationAttributeEval
  CorrelationAttributeEval :
  Evaluates the worth of an attribute by measuring the correlation (Pearson's) between it and the class.
  Nominal attributes are considered on a value by value basis by treating each value as an indicator.
  ErrorBasedMeritEvaluator
  Interface for evaluators that calculate the "merit" of attributes/subsets as the error of a learning scheme
  GainRatioAttributeEval
  GainRatioAttributeEval :
  Evaluates the worth of an attribute by measuring the gain ratio with respect to the class.
  GainR(Class, Attribute) = (H(Class) - H(Class | Attribute)) / H(Attribute).
  GreedyStepwise
  GreedyStepwise :
  Performs a greedy forward or backward search through the space of attribute subsets.
  HoldOutSubsetEvaluator
  Abstract attribute subset evaluator capable of evaluating subsets with respect to a data set that is distinct from that used to initialize/ train the subset evaluator.
  InfoGainAttributeEval
  InfoGainAttributeEval :
  Evaluates the worth of an attribute by measuring the information gain with respect to the class.
  InfoGain(Class,Attribute) = H(Class) - H(Class | Attribute).
  OneRAttributeEval
  OneRAttributeEval :
  Evaluates the worth of an attribute by using the OneR classifier.
  PrincipalComponents
  Performs a principal components analysis and transformation of the data.
  RankedOutputSearch
  Interface for search methods capable of producing a ranked list of attributes.
  Ranker
  Ranker :
  Ranks attributes by their individual evaluations.
  ReliefFAttributeEval
  ReliefFAttributeEval :
  Evaluates the worth of an attribute by repeatedly sampling an instance and considering the value of the given attribute for the nearest instance of the same and different class.
  StartSetHandler
  Interface for search methods capable of doing something sensible given a starting set of attributes.
  SubsetEvaluator
  Interface for attribute subset evaluators.
  SymmetricalUncertAttributeEval
  SymmetricalUncertAttributeEval :
  Evaluates the worth of an attribute by measuring the symmetrical uncertainty with respect to the class.
  UnsupervisedAttributeEvaluator
  Abstract unsupervised attribute evaluator.
  UnsupervisedSubsetEvaluator
  Abstract unsupervised attribute subset evaluator.
  WrapperSubsetEval
  WrapperSubsetEval:
  Evaluates attribute sets by using a learning scheme.