weka.classifiers.meta
Class MultiClassClassifier

java.lang.Object
  |
  +--weka.classifiers.Classifier
        |
        +--weka.classifiers.meta.MultiClassClassifier

All Implemented Interfaces:

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

public class MultiClassClassifier

extends Classifier

implements OptionHandler

Class for handling multi-class datasets with 2-class distribution classifiers.

Valid options are:

-M num
Sets the method to use. Valid values are 0 (1-against-all), 1 (random codes), 2 (exhaustive code), and 3 (1-against-1). (default 0)

-R num
Sets the multiplier when using random codes. (default 2.0)

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

-Q seed
Random number seed (default 1).

Version:

$Revision: 1.35 $

Author:

Eibe Frank (eibe@cs.waikato.ac.nz), Len Trigg (len@reeltwo.com), Richard Kirkby (rkirkby@cs.waikato.ac.nz)

See Also:

Serialized Form

Field Summary

static int	METHOD_1_AGAINST_1
static int	METHOD_1_AGAINST_ALL The error correction modes
static int	METHOD_ERROR_EXHAUSTIVE
static int	METHOD_ERROR_RANDOM
static Tag[]	TAGS_METHOD

Constructor Summary

MultiClassClassifier()

Method Summary

void	buildClassifier(Instances insts) Builds the classifiers.
java.lang.String	classifierTipText()
double[]	distributionForInstance(Instance inst) Returns the distribution for an instance.
Classifier	getClassifier() Get the classifier used as the classifier
SelectedTag	getMethod() Gets the method used.
java.lang.String[]	getOptions() Gets the current settings of the Classifier.
double	getRandomWidthFactor() Gets the multiplier when generating random codes.
int	getSeed() Gets the random number seed.
java.lang.String	globalInfo()
double[]	individualPredictions(Instance inst) Returns the individual predictions of the base classifiers for an instance.
java.util.Enumeration	listOptions() Returns an enumeration describing the available options
static void	main(java.lang.String[] argv) Main method for testing this class.
java.lang.String	methodTipText()
java.lang.String	randomWidthFactorTipText()
void	setClassifier(Classifier newClassifier) Set the base classifier.
void	setMethod(SelectedTag newMethod) Sets the method used.
void	setOptions(java.lang.String[] options) Parses a given list of options.
void	setRandomWidthFactor(double newRandomWidthFactor) Sets the multiplier when generating random codes.
void	setSeed(int seed) Sets the seed for random number generation.
java.lang.String	toString() Prints the classifiers.

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

Field Detail

METHOD_1_AGAINST_ALL

public static final int METHOD_1_AGAINST_ALL

The error correction modes

See Also:

Constant Field Values

METHOD_ERROR_RANDOM

public static final int METHOD_ERROR_RANDOM

See Also:

Constant Field Values

METHOD_ERROR_EXHAUSTIVE

public static final int METHOD_ERROR_EXHAUSTIVE

See Also:

Constant Field Values

METHOD_1_AGAINST_1

public static final int METHOD_1_AGAINST_1

See Also:

Constant Field Values

TAGS_METHOD

public static final Tag[] TAGS_METHOD

Constructor Detail

MultiClassClassifier

public MultiClassClassifier()

Method Detail

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

individualPredictions

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

Returns the individual predictions of the base classifiers for an instance. Used by StackedMultiClassClassifier. Returns the probability for the second "class" predicted by each base classifier.

Throws:

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

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

listOptions

public java.util.Enumeration listOptions()

Returns an enumeration describing 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 num
Sets the method to use. Valid values are 0 (1-against-all), 1 (random codes), 2 (exhaustive code), and 3 (1-against-1). (default 0)

-R num
Sets the multiplier when using random codes. (default 2.0)

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

-Q seed
Random number seed (default 1).

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.

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

randomWidthFactorTipText

public java.lang.String randomWidthFactorTipText()

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

getRandomWidthFactor

public double getRandomWidthFactor()

Gets the multiplier when generating random codes. Will generate numClasses * m_RandomWidthFactor codes.

Returns:

the width multiplier

setRandomWidthFactor

public void setRandomWidthFactor(double newRandomWidthFactor)

Sets the multiplier when generating random codes. Will generate numClasses * m_RandomWidthFactor codes.

Parameters:

newRandomWidthFactor - the new width multiplier

methodTipText

public java.lang.String methodTipText()

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

getMethod

public SelectedTag getMethod()

Gets the method used. Will be one of METHOD_1_AGAINST_ALL, METHOD_ERROR_RANDOM, METHOD_ERROR_EXHAUSTIVE, or METHOD_1_AGAINST_1.

Returns:

the current method.

setMethod

public void setMethod(SelectedTag newMethod)

Sets the method used. Will be one of METHOD_1_AGAINST_ALL, METHOD_ERROR_RANDOM, METHOD_ERROR_EXHAUSTIVE, or METHOD_1_AGAINST_1.

Parameters:

newMethod - the new method.

classifierTipText

public java.lang.String classifierTipText()

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

setClassifier

public void setClassifier(Classifier newClassifier)

Set the base classifier.

Parameters:

newClassifier - the Classifier to use.

getClassifier

public Classifier getClassifier()

Get the classifier used as the classifier

Returns:

the classifier used as the classifier

setSeed

public void setSeed(int seed)

Sets the seed for random number generation.

Parameters:

seed - the random number seed

getSeed

public int getSeed()

Gets the random number seed.

Returns:

the random number seed

main

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

Main method for testing this class.

Parameters:

argv - the options