weka.classifiers
Class MultiClassClassifier

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

All Implemented Interfaces:

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

public class MultiClassClassifier

extends DistributionClassifier

implements OptionHandler

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

Valid options are:

-E num
Sets the error-correction mode. Valid values are 0 (no correction), 1 (random codes), and 2 (exhaustive code). (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).

Author:

Eibe Frank (eibe@cs.waikato.ac.nz), Len Trigg (len@webmind.com)

See Also:

Serialized Form

Field Summary

static int	ERROR_EXHAUSTIVE
static int	ERROR_NONE The error correction modes
static int	ERROR_RANDOM
static Tag[]	TAGS_ERROR

Constructor Summary

MultiClassClassifier()

Method Summary

void	buildClassifier(Instances insts) Builds the classifiers.
java.lang.String	distributionClassifierTipText()
double[]	distributionForInstance(Instance inst) Returns the distribution for an instance.
java.lang.String	errorCorrectionModeTipText()
DistributionClassifier	getDistributionClassifier() Get the classifier used as the classifier
SelectedTag	getErrorCorrectionMode() Gets the error correction mode used.
java.lang.String[]	getOptions() Gets the current settings of the Classifier.
double	getRandomWidthFactor() Gets the multiplier when generating random codes.
java.lang.String	globalInfo()
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	randomWidthFactorTipText()
void	setDistributionClassifier(DistributionClassifier newClassifier) Set the base classifier.
void	setErrorCorrectionMode(SelectedTag newMethod) Sets the error correction mode used.
void	setOptions(java.lang.String[] options) Parses a given list of options.
void	setRandomWidthFactor(double newRandomWidthFactor) Sets the multiplier when generating random codes.
java.lang.String	toString() Prints the classifiers.

Methods inherited from class weka.classifiers.DistributionClassifier

classifyInstance

Methods inherited from class weka.classifiers.Classifier

forName, makeCopies

Methods inherited from class java.lang.Object

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

Field Detail

ERROR_NONE

public static final int ERROR_NONE

The error correction modes

ERROR_RANDOM

public static final int ERROR_RANDOM

ERROR_EXHAUSTIVE

public static final int ERROR_EXHAUSTIVE

TAGS_ERROR

public static final Tag[] TAGS_ERROR

Constructor Detail

MultiClassClassifier

public MultiClassClassifier()

Method Detail

buildClassifier

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

Builds the classifiers.

Overrides:

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 DistributionClassifier

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

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:

-E num
Sets the error-correction mode. Valid values are 0 (no correction), 1 (random codes), and 2 (exhaustive code). (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).

Specified by:

setOptions in interface OptionHandler

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

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

errorCorrectionModeTipText

public java.lang.String errorCorrectionModeTipText()

Returns:

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

getErrorCorrectionMode

public SelectedTag getErrorCorrectionMode()

Gets the error correction mode used. Will be one of ERROR_NONE, ERROR_RANDOM, or ERROR_EXHAUSTIVE.

Returns:

the current error correction mode.

setErrorCorrectionMode

public void setErrorCorrectionMode(SelectedTag newMethod)

Sets the error correction mode used. Will be one of ERROR_NONE, ERROR_RANDOM, or ERROR_EXHAUSTIVE.

Parameters:

newMethod - the new error correction mode.

distributionClassifierTipText

public java.lang.String distributionClassifierTipText()

Returns:

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

setDistributionClassifier

public void setDistributionClassifier(DistributionClassifier newClassifier)

Set the base classifier.

Parameters:

newClassifier - the Classifier to use.

getDistributionClassifier

public DistributionClassifier getDistributionClassifier()

Get the classifier used as the classifier

Returns:

the classifier used as the classifier

main

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

Main method for testing this class.

Parameters:

argv - the options