weka.classifiers.trees.j48

Class ClassifierSplitModel

java.lang.Object

weka.classifiers.trees.j48.ClassifierSplitModel

All Implemented Interfaces:

Serializable, Cloneable, RevisionHandler

Direct Known Subclasses:

BinC45Split, C45Split, NBTreeNoSplit, NBTreeSplit, NoSplit, ResidualSplit

public abstract class ClassifierSplitModel
extends Object
implements Cloneable, Serializable, RevisionHandler

Abstract class for classification models that can be used recursively to split the data.

Version:

$Revision: 8034 $

Author:

Eibe Frank (eibe@cs.waikato.ac.nz)

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
ClassifierSplitModel()

Method Summary

Methods

Modifier and Type	Method and Description
abstract void	buildClassifier(Instances instances) Builds the classifier split model for the given set of instances.
boolean	checkModel() Checks if generated model is valid.
double	classifyInstance(Instance instance) Classifies a given instance.
double	classProb(int classIndex, Instance instance, int theSubset) Gets class probability for instance.
double	classProbLaplace(int classIndex, Instance instance, int theSubset) Gets class probability for instance.
Object	clone() Allows to clone a model (shallow copy).
double	codingCost() Returns coding costs of model.
Distribution	distribution() Returns the distribution of class values induced by the model.
String	dumpLabel(int index, Instances data) Prints label for subset index of instances (eg class).
String	dumpModel(Instances data) Prints the split model.
abstract String	leftSide(Instances data) Prints left side of condition satisfied by instances.
int	numSubsets() Returns the number of created subsets for the split.
void	resetDistribution(Instances data) Sets distribution associated with model.
abstract String	rightSide(int index, Instances data) Prints left side of condition satisfied by instances in subset index.
String	sourceClass(int index, Instances data)
abstract String	sourceExpression(int index, Instances data)
Instances[]	split(Instances data) Splits the given set of instances into subsets.
abstract double[]	weights(Instance instance) Returns weights if instance is assigned to more than one subset.
abstract int	whichSubset(Instance instance) Returns index of subset instance is assigned to.

Methods inherited from class java.lang.Object

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

Methods inherited from interface weka.core.RevisionHandler

getRevision

Constructor Detail

ClassifierSplitModel

public ClassifierSplitModel()

Method Detail

clone

public Object clone()

Allows to clone a model (shallow copy).

Overrides:

clone in class Object

buildClassifier

public abstract void buildClassifier(Instances instances)
                              throws Exception

Builds the classifier split model for the given set of instances.

Throws:

Exception - if something goes wrong

checkModel

public final boolean checkModel()

Checks if generated model is valid.

classifyInstance

public final double classifyInstance(Instance instance)
                              throws Exception

Classifies a given instance.

Throws:

Exception - if something goes wrong

classProb

public double classProb(int classIndex,
               Instance instance,
               int theSubset)
                 throws Exception

Gets class probability for instance.

Throws:

Exception - if something goes wrong

classProbLaplace

public double classProbLaplace(int classIndex,
                      Instance instance,
                      int theSubset)
                        throws Exception

Gets class probability for instance.

Throws:

Exception - if something goes wrong

codingCost

public double codingCost()

Returns coding costs of model. Returns 0 if not overwritten.

distribution

public final Distribution distribution()

Returns the distribution of class values induced by the model.

leftSide

public abstract String leftSide(Instances data)

Prints left side of condition satisfied by instances.

Parameters:

data - the data.

rightSide

public abstract String rightSide(int index,
               Instances data)

Prints left side of condition satisfied by instances in subset index.

dumpLabel

public final String dumpLabel(int index,
               Instances data)
                       throws Exception

Prints label for subset index of instances (eg class).

Throws:

Exception - if something goes wrong

sourceClass

public final String sourceClass(int index,
                 Instances data)
                         throws Exception

Throws:

Exception

sourceExpression

public abstract String sourceExpression(int index,
                      Instances data)

dumpModel

public final String dumpModel(Instances data)
                       throws Exception

Prints the split model.

Throws:

Exception - if something goes wrong

numSubsets

public final int numSubsets()

Returns the number of created subsets for the split.

resetDistribution

public void resetDistribution(Instances data)
                       throws Exception

Sets distribution associated with model.

Throws:

Exception

split

public final Instances[] split(Instances data)
                        throws Exception

Splits the given set of instances into subsets.

Throws:

Exception - if something goes wrong

weights

public abstract double[] weights(Instance instance)

Returns weights if instance is assigned to more than one subset. Returns null if instance is only assigned to one subset.

whichSubset

public abstract int whichSubset(Instance instance)
                         throws Exception

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

Throws:

Exception - if something goes wrong