weka.classifiers.meta
Class StackingC

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

All Implemented Interfaces:

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

public class StackingC

extends Stacking

implements OptionHandler

Implements StackingC (more efficient version of stacking). For more information, see

Seewald A.K.: How to Make Stacking Better and Faster While Also Taking Care of an Unknown Weakness, in Sammut C., Hoffmann A. (eds.), Proceedings of the Nineteenth International Conference on Machine Learning (ICML 2002), Morgan Kaufmann Publishers, pp.554-561, 2002.

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. Has to be a numeric prediction scheme, defaults to Linear Regression as in the original paper.

Version:

$Revision: 1.8 $

Author:

Eibe Frank (eibe@cs.waikato.ac.nz), Alexander K. Seewald (alex@seewald.at)

See Also:

Serialized Form

Field Summary

protected Remove	m_attrFilter Filters to transform metaData
protected MakeIndicator	m_makeIndicatorFilter
protected Classifier[]	m_MetaClassifiers The meta classifiers (one for each class, like in ClassificationViaRegression)

Fields inherited from class weka.classifiers.meta.Stacking

m_BaseFormat, m_MetaClassifier, m_MetaFormat, m_NumFolds

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

StackingC()
The constructor.

Method Summary

double[]	distributionForInstance(Instance instance) Classifies a given instance using the stacked classifier.
protected void	generateMetaLevel(Instances newData, java.util.Random random) Method that builds meta level.
java.lang.String	globalInfo() Returns a string describing classifier
static void	main(java.lang.String[] argv) Main method for testing this class.
protected java.lang.String	metaOption() String describing option for setting meta classifier
protected void	processMetaOptions(java.lang.String[] options) Process options setting meta classifier.
java.lang.String	toString() Output a representation of this classifier

Methods inherited from class weka.classifiers.meta.Stacking

buildClassifier, getMetaClassifier, getNumFolds, getOptions, listOptions, metaClassifierTipText, metaFormat, metaInstance, numFoldsTipText, setMetaClassifier, setNumFolds, setOptions

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

Methods inherited from interface weka.core.OptionHandler

getOptions, listOptions, setOptions

Field Detail

m_MetaClassifiers

protected Classifier[] m_MetaClassifiers

The meta classifiers (one for each class, like in ClassificationViaRegression)

m_attrFilter

protected Remove m_attrFilter

Filters to transform metaData

m_makeIndicatorFilter

protected MakeIndicator m_makeIndicatorFilter

Constructor Detail

StackingC

public StackingC()

The constructor.

Method Detail

globalInfo

public java.lang.String globalInfo()

Returns a string describing classifier

Overrides:

globalInfo in class Stacking

Returns:

a description suitable for displaying in the explorer/experimenter gui

metaOption

protected java.lang.String metaOption()

String describing option for setting meta classifier

Overrides:

metaOption in class Stacking

processMetaOptions

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

Process options setting meta classifier.

Overrides:

processMetaOptions in class Stacking

Throws:

java.lang.Exception

generateMetaLevel

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

Method that builds meta level.

Overrides:

generateMetaLevel in class Stacking

Throws:

java.lang.Exception

distributionForInstance

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

Classifies a given instance using the stacked classifier.

Overrides:

distributionForInstance in class Stacking

Parameters:

instance - the instance to be classified

Throws:

java.lang.Exception - if instance could not be classified successfully

toString

public java.lang.String toString()

Output a representation of this classifier

Overrides:

toString in class Stacking

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]