weka.classifiers.meta
Class Stacking

java.lang.Object
  extended by weka.classifiers.Classifier
      extended by weka.classifiers.MultipleClassifiersCombiner
          extended by weka.classifiers.RandomizableMultipleClassifiersCombiner
              extended by weka.classifiers.meta.Stacking
All Implemented Interfaces:
java.io.Serializable, java.lang.Cloneable, CapabilitiesHandler, OptionHandler, Randomizable, RevisionHandler, TechnicalInformationHandler
Direct Known Subclasses:
Grading, StackingC

public class Stacking
extends RandomizableMultipleClassifiersCombiner
implements TechnicalInformationHandler

Combines several classifiers using the stacking method. Can do classification or regression.

For more information, see

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

BibTeX:

 @article{Wolpert1992,
    author = {David H. Wolpert},
    journal = {Neural Networks},
    pages = {241-259},
    publisher = {Pergamon Press},
    title = {Stacked generalization},
    volume = {5},
    year = {1992}
 }
 

Valid options are:

 -M <scheme specification>
  Full name of meta classifier, followed by options.
  (default: "weka.classifiers.rules.Zero")
 -X <number of folds>
  Sets the number of cross-validation folds.
 -S <num>
  Random number seed.
  (default 1)
 -B <classifier specification>
  Full class name of classifier to include, followed
  by scheme options. May be specified multiple times.
  (default: "weka.classifiers.rules.ZeroR")
 -D
  If set, classifier is run in debug mode and
  may output additional info to the console

Version:
$Revision: 6996 $
Author:
Eibe Frank ([email protected])
See Also:
Serialized Form

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.
 Capabilities getCapabilities()
          Returns combined capabilities of the base classifiers, i.e., the capabilities all of them have in common.
 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 getRevision()
          Returns the revision string.
 TechnicalInformation getTechnicalInformation()
          Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
 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
 java.lang.String numFoldsTipText()
          Returns the tip text for this property
 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, setClassifiers
 
Methods inherited from class weka.classifiers.Classifier
classifyInstance, debugTipText, forName, getDebug, makeCopies, makeCopy, setDebug
 
Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait
 

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

getTechnicalInformation

public TechnicalInformation getTechnicalInformation()
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

Specified by:
getTechnicalInformation in interface TechnicalInformationHandler
Returns:
the technical information about this class

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.

setOptions

public void setOptions(java.lang.String[] options)
                throws java.lang.Exception
Parses a given list of options.

Valid options are:

 -M <scheme specification>
  Full name of meta classifier, followed by options.
  (default: "weka.classifiers.rules.Zero")
 -X <number of folds>
  Sets the number of cross-validation folds.
 -S <num>
  Random number seed.
  (default 1)
 -B <classifier specification>
  Full class name of classifier to include, followed
  by scheme options. May be specified multiple times.
  (default: "weka.classifiers.rules.ZeroR")
 -D
  If set, classifier is run in debug mode and
  may output additional info to the console

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

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

getCapabilities

public Capabilities getCapabilities()
Returns combined capabilities of the base classifiers, i.e., the capabilities all of them have in common.

Specified by:
getCapabilities in interface CapabilitiesHandler
Overrides:
getCapabilities in class MultipleClassifiersCombiner
Returns:
the capabilities of the base classifiers
See Also:
Capabilities

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

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:
the distribution
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 java.lang.Object
Returns:
a string representation of the classifier

getRevision

public java.lang.String getRevision()
Returns the revision string.

Specified by:
getRevision in interface RevisionHandler
Overrides:
getRevision in class Classifier
Returns:
the revision

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]