Package weka.classifiers.pmml.producer

# Class LogisticProducerHelper

java.lang.Object
weka.classifiers.pmml.producer.AbstractPMMLProducerHelper
weka.classifiers.pmml.producer.LogisticProducerHelper

public class LogisticProducerHelper extends AbstractPMMLProducerHelper
Helper class for producing PMML for a Logistic classifier. Not designed to be used directly - you should call toPMML() on a trained Logistic classifier.

Version:
  $Revision: $
Author:
  David Persons, Mark Hall (mhall{[at]}pentaho{[dot]}com)

- ## Field Summary

  ### Fields inherited from class weka.classifiers.pmml.producer.AbstractPMMLProducerHelper

  `PMML_VERSION`

- ## Constructor Summary

  Constructors
  Constructor
  Description
  `LogisticProducerHelper()`

- ## Method Summary

  Modifier and Type
  Method
  Description
  `static String`
  `toPMML(Instances train, Instances structureAfterFiltering, double[][] par, int numClasses)`
  Produce the PMML for a Logistic classifier

  ### Methods inherited from class weka.classifiers.pmml.producer.AbstractPMMLProducerHelper

  `addDataDictionary, getNameAndValueFromUnsupervisedNominalToBinaryDerivedAttribute, getOPTYPE, initPMML`

  ### Methods inherited from class java.lang.Object

  `equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

- ## Constructor Details

  - ### LogisticProducerHelper

    public LogisticProducerHelper()

- ## Method Details

  - ### toPMML

    public static String toPMML(Instances train, Instances structureAfterFiltering, double[][] par, int numClasses)
    Produce the PMML for a Logistic classifier
    Parameters:
      `train` - the training data used to build the Logistic model
      `structureAfterFiltering` - the structure of the training data after filtering
      `par` - the parameters of the function(s)
      `numClasses` - the number of classes in the data
    Returns:
      the PMML for the classifier