weka.classifiers.meta
Class TreeBasedMultiClassClassifier

java.lang.Object
  weka.classifiers.Classifier
      weka.classifiers.meta.TreeBasedMultiClassClassifier

All Implemented Interfaces:

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

public class TreeBasedMultiClassClassifier

extends Classifier

implements OptionHandler, Randomizable

Class that represents and builds a classifier tree.

See Also:

Serialized Form

Field Summary

protected Classifier	m_Classifier The classifier at this node.
protected boolean	m_ClassIsOrdinal Whether class is ordinal
(package private) Instances	m_Data
protected MakeIndicator	m_Filter The filter used at this node
protected TreeBasedMultiClassClassifier	m_FirstSuccessor The first successor
protected java.util.Random	m_Random The random number generator.
protected Range	m_Range The classes that are grouped together at the current node
protected TreeBasedMultiClassClassifier	m_SecondSuccessor The second successor
protected int	m_Seed Random number seed
protected boolean	m_UseRandomSelection Whether to split classes randomly

Fields inherited from class weka.classifiers.Classifier

m_Debug

Constructor Summary

TreeBasedMultiClassClassifier()

Method Summary

void	buildClassifier(Instances data) Builds tree recursively
double[]	distributionForInstance(Instance inst) Predicts the class distribution for a given instance * * @param inst the (multi-class) instance to be classified
private void	generateClassifierForNode(Instances data, Range classes, java.util.Random rand, Classifier classifier, boolean random, boolean ordinal) Generates a classifier for the current node and proceeds recursively
Classifier	getClassifier() Get the classifier used as the classifier * * @return the classifier used as the classifier
boolean	getClassOrdinal() Get whether class is ordinal.
java.lang.String[]	getOptions() Gets the current settings of the Classifier
boolean	getRandomSelection() Get whether to perform a random selection.
int	getSeed() Gets the random number seed
java.lang.String	globalInfo()
java.util.Enumeration	listOptions() Returns an enumeration describing the available options * * @return an enumeration of all the available options
static void	main(java.lang.String[] argv) Main method for testing this class
void	setClassifier(Classifier newClassifier) Set the base classifier
void	setClassOrdinal(boolean v) Set whether class is ordinal.
void	setOptions(java.lang.String[] options) Parses a given list of options.
void	setRandomSelection(boolean v) Set whether to perform a random selection.
void	setSeed(int seed) Sets the seed for random number generation
java.lang.String	toString() Outputs the classifier as a string.
private int	treeToString(java.lang.StringBuffer text, int nn) Returns string description of the tree.

Methods inherited from class weka.classifiers.Classifier

classifyInstance, debugTipText, forName, getDebug, makeCopies, setDebug

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Detail

m_Classifier

protected Classifier m_Classifier

The classifier at this node.

m_Filter

protected MakeIndicator m_Filter

The filter used at this node

m_FirstSuccessor

protected TreeBasedMultiClassClassifier m_FirstSuccessor

The first successor

m_SecondSuccessor

protected TreeBasedMultiClassClassifier m_SecondSuccessor

The second successor

m_Random

protected java.util.Random m_Random

The random number generator.

m_Range

protected Range m_Range

The classes that are grouped together at the current node

m_UseRandomSelection

protected boolean m_UseRandomSelection

Whether to split classes randomly

m_ClassIsOrdinal

protected boolean m_ClassIsOrdinal

Whether class is ordinal

m_Seed

protected int m_Seed

Random number seed

m_Data

Instances m_Data

Constructor Detail

TreeBasedMultiClassClassifier

public TreeBasedMultiClassClassifier()

Method Detail

generateClassifierForNode

private void generateClassifierForNode(Instances data,
                                       Range classes,
                                       java.util.Random rand,
                                       Classifier classifier,
                                       boolean random,
                                       boolean ordinal)
                                throws java.lang.Exception

Generates a classifier for the current node and proceeds recursively. * * @param data contains the (multi-class) instances * @param classes contains the indices of the classes that are present

Throws:

java.lang.Exception

buildClassifier

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

Builds tree recursively. * * @param data contains the (multi-class) instances

Specified by:

buildClassifier in class Classifier

Parameters:

data - set of instances serving as training data

Throws:

java.lang.Exception - if the classifier has not been generated successfully

distributionForInstance

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

Predicts the class distribution for a given instance * * @param inst the (multi-class) instance to be classified

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 distribution could not be computed successfully

listOptions

public java.util.Enumeration listOptions()

Returns an enumeration describing the available options * * @return an enumeration of all the available options

Specified by:

listOptions in interface OptionHandler

Overrides:

listOptions in class Classifier

Returns:

an enumeration of all the available options.

setOptions

public void setOptions(java.lang.String[] options)
                throws java.lang.Exception

Parses a given list of options. Valid options are:

* * -M
* Sets whether Sets whether class is ordinal (default: nominal).

* * -R
* Sets whether selection is random (default: deterministic)

* * -W classname
* Specify the full class name of a learner as the basis for * the multiclassclassifier (required).

* * -Q seed
* Random number seed (default 1).

* * @param options the list of options as an array of strings * @exception Exception if an option is not supported

Specified by:

setOptions in interface OptionHandler

Overrides:

setOptions in class Classifier

Parameters:

options - the list of options as an array of strings

Throws:

java.lang.Exception - if an option is not supported

getOptions

public java.lang.String[] getOptions()

Gets the current settings of the Classifier. * * @return an array of strings suitable for passing to setOptions

Specified by:

getOptions in interface OptionHandler

Overrides:

getOptions in class Classifier

Returns:

an array of strings suitable for passing to setOptions

globalInfo

public java.lang.String globalInfo()

Returns:

a description of the classifier suitable for * displaying in the explorer/experimenter gui

setRandomSelection

public void setRandomSelection(boolean v)

Set whether to perform a random selection.

getRandomSelection

public boolean getRandomSelection()

Get whether to perform a random selection.

setClassOrdinal

public void setClassOrdinal(boolean v)

Set whether class is ordinal.

getClassOrdinal

public boolean getClassOrdinal()

Get whether class is ordinal.

setSeed

public void setSeed(int seed)

Sets the seed for random number generation. * * @param seed the random number seed

Specified by:

setSeed in interface Randomizable

Parameters:

seed - the seed

getSeed

public int getSeed()

Gets the random number seed. * * @return the random number seed

Specified by:

getSeed in interface Randomizable

Returns:

the seed for the random number generation

setClassifier

public void setClassifier(Classifier newClassifier)

Set the base classifier. * * @param newClassifier the Classifier to use.

getClassifier

public Classifier getClassifier()

Get the classifier used as the classifier * * @return the classifier used as the classifier

toString

public java.lang.String toString()

Outputs the classifier as a string.

treeToString

private int treeToString(java.lang.StringBuffer text,
                         int nn)

Returns string description of the tree.

main

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

Main method for testing this class. * * @param argv the options