weka.classifiers.trees.lmt

Class ResidualSplit

java.lang.Object

weka.classifiers.trees.j48.ClassifierSplitModel

weka.classifiers.trees.lmt.ResidualSplit

All Implemented Interfaces:

java.io.Serializable, java.lang.Cloneable, RevisionHandler

public class ResidualSplit
extends ClassifierSplitModel

Helper class for logistic model trees (weka.classifiers.trees.lmt.LMT) to implement the splitting criterion based on residuals of the LogitBoost algorithm.

Version:

$Revision: 1.4 $

Author:

Niels Landwehr

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
ResidualSplit(int attIndex) Creates a split object

Method Summary

Modifier and Type	Method and Description
void	buildClassifier(Instances data) Method not in use
void	buildClassifier(Instances data, double[][] dataZs, double[][] dataWs) Builds the split.
boolean	checkModel(int minNumInstances) Checks if there are at least 2 subsets that contain >= minNumInstances.
double	entropyGain() Computes entropy gain for current split.
java.lang.String	getRevision() Returns the revision string.
java.lang.String	leftSide(Instances data) Returns name of splitting attribute (left side of condition).
java.lang.String	rightSide(int index, Instances data) Prints the condition satisfied by instances in a subset.
java.lang.String	sourceExpression(int index, Instances data) Method not in use
double[]	weights(Instance instance) Method not in use
int	whichSubset(Instance instance) Returns index of subset instance is assigned to.

Methods inherited from class weka.classifiers.trees.j48.ClassifierSplitModel

checkModel, classifyInstance, classProb, classProbLaplace, clone, codingCost, distribution, dumpLabel, dumpModel, numSubsets, resetDistribution, sourceClass, split

Methods inherited from class java.lang.Object

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

Constructor Detail

ResidualSplit

public ResidualSplit(int attIndex)

Creates a split object

Parameters:

attIndex - the index of the attribute to split on

Method Detail

buildClassifier

public void buildClassifier(Instances data,
                            double[][] dataZs,
                            double[][] dataWs)
                     throws java.lang.Exception

Builds the split. Needs the Z/W values of LogitBoost for the set of instances.

Throws:

java.lang.Exception

entropyGain

public double entropyGain()
                   throws java.lang.Exception

Computes entropy gain for current split.

Throws:

java.lang.Exception

checkModel

public boolean checkModel(int minNumInstances)

Checks if there are at least 2 subsets that contain >= minNumInstances.

leftSide

public final java.lang.String leftSide(Instances data)

Returns name of splitting attribute (left side of condition).

Specified by:

leftSide in class ClassifierSplitModel

Parameters:

data - the data.

rightSide

public final java.lang.String rightSide(int index,
                                        Instances data)

Prints the condition satisfied by instances in a subset.

Specified by:

rightSide in class ClassifierSplitModel

whichSubset

public final int whichSubset(Instance instance)
                      throws java.lang.Exception

Description copied from class: ClassifierSplitModel

Returns index of subset instance is assigned to. Returns -1 if instance is assigned to more than one subset.

Specified by:

whichSubset in class ClassifierSplitModel

Throws:

java.lang.Exception - if something goes wrong

buildClassifier

public void buildClassifier(Instances data)

Method not in use

Specified by:

buildClassifier in class ClassifierSplitModel

weights

public final double[] weights(Instance instance)

Method not in use

Specified by:

weights in class ClassifierSplitModel

sourceExpression

public final java.lang.String sourceExpression(int index,
                                               Instances data)

Method not in use

Specified by:

sourceExpression in class ClassifierSplitModel

getRevision

public java.lang.String getRevision()

Returns the revision string.

Returns:

the revision