weka.classifiers.meta
Class ClassificationViaRegression

java.lang.Object
  weka.classifiers.Classifier
      weka.classifiers.SingleClassifierEnhancer
          weka.classifiers.meta.ClassificationViaRegression

All Implemented Interfaces:

java.lang.Cloneable, OptionHandler, java.io.Serializable

public class ClassificationViaRegression

extends SingleClassifierEnhancer

Class for doing classification using regression methods. For more information, see

E. Frank, Y. Wang, S. Inglis, G. Holmes, and I.H. Witten (1998) "Using model trees for classification", Machine Learning, Vol.32, No.1, pp. 63-76.

Valid options are:

-W classname
Specify the full class name of a numeric predictor as the basis for the classifier (required).

Version:

$Revision: 1.20 $

Author:

Eibe Frank (eibe@cs.waikato.ac.nz), Len Trigg (trigg@cs.waikato.ac.nz)

See Also:

Serialized Form

Constructor Summary

ClassificationViaRegression()
Default constructor.

Method Summary

void	buildClassifier(Instances insts) Builds the classifiers.
double[]	distributionForInstance(Instance inst) Returns the distribution for an instance.
java.lang.String	globalInfo() Returns a string describing classifier
static void	main(java.lang.String[] argv) Main method for testing this class.
java.lang.String	toString() Prints the classifiers.

Methods inherited from class weka.classifiers.SingleClassifierEnhancer

classifierTipText, getClassifier, getOptions, listOptions, setClassifier, setOptions

Methods inherited from class weka.classifiers.Classifier

classifyInstance, debugTipText, forName, getDebug, makeCopies, setDebug

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

ClassificationViaRegression

public ClassificationViaRegression()

Default constructor.

Method Detail

globalInfo

public java.lang.String globalInfo()

Returns a string describing classifier

Returns:

a description suitable for displaying in the explorer/experimenter gui

buildClassifier

public void buildClassifier(Instances insts)
                     throws java.lang.Exception

Builds the classifiers.

Specified by:

buildClassifier in class Classifier

Parameters:

insts - the training data.

Throws:

java.lang.Exception - if a classifier can't be built

distributionForInstance

public double[] distributionForInstance(Instance inst)
                                 throws java.lang.Exception

Returns the distribution for an instance.

Overrides:

distributionForInstance in class Classifier

Parameters:

inst - the instance to be classified

Returns:

an array containing the estimated membership probabilities of the test instance in each class or the numeric prediction

Throws:

java.lang.Exception - if the distribution can't be computed successfully

toString

public java.lang.String toString()

Prints the classifiers.

main

public static void main(java.lang.String[] argv)

Main method for testing this class.

Parameters:

argv - the options for the learner