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.

Overrides:
toString in class java.lang.Object

main

public static void main(java.lang.String[] argv)
Main method for testing this class.

Parameters:
argv - the options for the learner


Copyright (c) 2003 David Lindsay, Computer Learning Research Centre, Dept. Computer Science, Royal Holloway, University of London