weka.classifiers.meta
Class Stacking

java.lang.Object
  weka.classifiers.Classifier
      weka.classifiers.MultipleClassifiersCombiner
          weka.classifiers.RandomizableMultipleClassifiersCombiner
              weka.classifiers.meta.Stacking

All Implemented Interfaces:

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

Direct Known Subclasses:

Grading, StackingC

public class Stacking

extends RandomizableMultipleClassifiersCombiner

Implements stacking. For more information, see

David H. Wolpert (1992). Stacked generalization. Neural Networks, 5:241-259, Pergamon Press.

Valid options are:

-X num_folds
The number of folds for the cross-validation (default 10).

-S seed
Random number seed (default 1).

-B classifierstring
Classifierstring should contain the full class name of a base scheme followed by options to the classifier. (required, option should be used once for each classifier).

-M classifierstring
Classifierstring for the meta classifier. Same format as for base classifiers. (required)

Version:

$Revision: 1.22 $

Author:

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

See Also:

Serialized Form

Field Summary

protected Instances	m_BaseFormat Format for base data
protected Classifier	m_MetaClassifier The meta classifier
protected Instances	m_MetaFormat Format for meta data
protected int	m_NumFolds Set the number of folds for the cross-validation

Fields inherited from class weka.classifiers.RandomizableMultipleClassifiersCombiner

m_Seed

Fields inherited from class weka.classifiers.MultipleClassifiersCombiner

m_Classifiers

Fields inherited from class weka.classifiers.Classifier

m_Debug

Constructor Summary

Stacking()

Method Summary

void	buildClassifier(Instances data) Buildclassifier selects a classifier from the set of classifiers by minimising error on the training data.
double[]	distributionForInstance(Instance instance) Returns class probabilities.
protected void	generateMetaLevel(Instances newData, java.util.Random random) Generates the meta data
Classifier	getMetaClassifier() Gets the meta classifier.
int	getNumFolds() Gets the number of folds for the cross-validation.
java.lang.String[]	getOptions() Gets the current settings of the Classifier.
java.lang.String	globalInfo() Returns a string describing classifier
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	metaClassifierTipText() Returns the tip text for this property
protected Instances	metaFormat(Instances instances) Makes the format for the level-1 data.
protected Instance	metaInstance(Instance instance) Makes a level-1 instance from the given instance.
protected java.lang.String	metaOption() String describing option for setting meta classifier
java.lang.String	numFoldsTipText() Returns the tip text for this property
protected void	processMetaOptions(java.lang.String[] options) Process options setting meta classifier.
void	setMetaClassifier(Classifier classifier) Adds meta classifier
void	setNumFolds(int numFolds) Sets the number of folds for the cross-validation.
void	setOptions(java.lang.String[] options) Parses a given list of options.
java.lang.String	toString() Output a representation of this classifier

Methods inherited from class weka.classifiers.RandomizableMultipleClassifiersCombiner

getSeed, seedTipText, setSeed

Methods inherited from class weka.classifiers.MultipleClassifiersCombiner

classifiersTipText, getClassifier, getClassifiers, getClassifierSpec, setClassifiers

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_MetaClassifier

protected Classifier m_MetaClassifier

The meta classifier

m_MetaFormat

protected Instances m_MetaFormat

Format for meta data

m_BaseFormat

protected Instances m_BaseFormat

Format for base data

m_NumFolds

protected int m_NumFolds

Set the number of folds for the cross-validation

Constructor Detail

Stacking

public Stacking()

Method Detail

globalInfo

public java.lang.String globalInfo()

Returns a string describing classifier

Returns:

a description suitable for displaying in the explorer/experimenter gui

listOptions

public java.util.Enumeration listOptions()

Returns an enumeration describing the available options.

Specified by:

listOptions in interface OptionHandler

Overrides:

listOptions in class RandomizableMultipleClassifiersCombiner

Returns:

an enumeration of all the available options.

metaOption

protected java.lang.String metaOption()

String describing option for setting meta classifier

setOptions

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

Parses a given list of options. Valid options are:

-X num_folds
The number of folds for the cross-validation (default 10).

-S seed
Random number seed (default 1).

-B classifierstring
Classifierstring should contain the full class name of a base scheme followed by options to the classifier. (required, option should be used once for each classifier).

-M classifierstring
Classifierstring for the meta classifier. Same format as for base classifiers. (default: weka.classifiers.rules.ZeroR)

Specified by:

setOptions in interface OptionHandler

Overrides:

setOptions in class RandomizableMultipleClassifiersCombiner

Parameters:

options - the list of options as an array of strings

Throws:

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

processMetaOptions

protected void processMetaOptions(java.lang.String[] options)
                           throws java.lang.Exception

Process options setting meta classifier.

Throws:

java.lang.Exception

getOptions

public java.lang.String[] getOptions()

Gets the current settings of the Classifier.

Specified by:

getOptions in interface OptionHandler

Overrides:

getOptions in class RandomizableMultipleClassifiersCombiner

Returns:

an array of strings suitable for passing to setOptions

numFoldsTipText

public java.lang.String numFoldsTipText()

Returns the tip text for this property

Returns:

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

getNumFolds

public int getNumFolds()

Gets the number of folds for the cross-validation.

Returns:

the number of folds for the cross-validation

setNumFolds

public void setNumFolds(int numFolds)
                 throws java.lang.Exception

Sets the number of folds for the cross-validation.

Parameters:

numFolds - the number of folds for the cross-validation

Throws:

java.lang.Exception - if parameter illegal

metaClassifierTipText

public java.lang.String metaClassifierTipText()

Returns the tip text for this property

Returns:

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

setMetaClassifier

public void setMetaClassifier(Classifier classifier)

Adds meta classifier

Parameters:

classifier - the classifier with all options set.

getMetaClassifier

public Classifier getMetaClassifier()

Gets the meta classifier.

Returns:

the meta classifier

buildClassifier

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

Buildclassifier selects a classifier from the set of classifiers by minimising error on the training data.

Specified by:

buildClassifier in class Classifier

Parameters:

data - the training data to be used for generating the boosted classifier.

Throws:

java.lang.Exception - if the classifier could not be built successfully

generateMetaLevel

protected void generateMetaLevel(Instances newData,
                                 java.util.Random random)
                          throws java.lang.Exception

Generates the meta data

Throws:

java.lang.Exception

distributionForInstance

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

Returns class probabilities.

Overrides:

distributionForInstance in class Classifier

Parameters:

instance - 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 instance could not be classified successfully

toString

public java.lang.String toString()

Output a representation of this classifier

metaFormat

protected Instances metaFormat(Instances instances)
                        throws java.lang.Exception

Makes the format for the level-1 data.

Parameters:

instances - the level-0 format

Returns:

the format for the meta data

Throws:

java.lang.Exception

metaInstance

protected Instance metaInstance(Instance instance)
                         throws java.lang.Exception

Makes a level-1 instance from the given instance.

Parameters:

instance - the instance to be transformed

Returns:

the level-1 instance

Throws:

java.lang.Exception

main

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

Main method for testing this class.

Parameters:

argv - should contain the following arguments: -t training file [-T test file] [-c class index]