weka.classifiers.meta

## Class Stacking

- java.lang.Object
- - weka.classifiers.AbstractClassifier
  - - weka.classifiers.MultipleClassifiersCombiner
    - - weka.classifiers.ParallelMultipleClassifiersCombiner
      - - weka.classifiers.RandomizableParallelMultipleClassifiersCombiner
        - - weka.classifiers.meta.Stacking

- All Implemented Interfaces:
    java.io.Serializable, java.lang.Cloneable, Classifier, CapabilitiesHandler, CapabilitiesIgnorer, OptionHandler, Randomizable, RevisionHandler, TechnicalInformationHandler

      public class Stacking
      extends RandomizableParallelMultipleClassifiersCombiner
      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: 10141 $
  Author:
    Eibe Frank (eibe@cs.waikato.ac.nz)
  See Also:
    Serialized Form

- - ### Constructor Summary

    Constructors
    Constructor and Description
    `Stacking()`

  - ### Method Summary

    Methods
    Modifier and Type | Method and Description
    --- | ---
    `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<Option>` | `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.RandomizableParallelMultipleClassifiersCombiner

      `getSeed, seedTipText, setSeed`

    - ### Methods inherited from class weka.classifiers.ParallelMultipleClassifiersCombiner

      `getNumExecutionSlots, numExecutionSlotsTipText, setNumExecutionSlots`

    - ### Methods inherited from class weka.classifiers.MultipleClassifiersCombiner

      `classifiersTipText, getClassifier, getClassifiers, setClassifiers`

    - ### Methods inherited from class weka.classifiers.AbstractClassifier

      `classifyInstance, debugTipText, doNotCheckCapabilitiesTipText, forName, getDebug, getDoNotCheckCapabilities, makeCopies, makeCopy, runClassifier, setDebug, setDoNotCheckCapabilities`

    - ### 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<Option> listOptions()

      Returns an enumeration describing the available options.
      Specified by:
        `listOptions` in interface `OptionHandler`
      Overrides:
        `listOptions` in class `RandomizableParallelMultipleClassifiersCombiner`
      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 `RandomizableParallelMultipleClassifiersCombiner`
      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 `RandomizableParallelMultipleClassifiersCombiner`
      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 `Classifier`
      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 interface `Classifier`
      Overrides:
        `buildClassifier` in class `ParallelMultipleClassifiersCombiner`
      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.
      Specified by:
        `distributionForInstance` in interface `Classifier`
      Overrides:
        `distributionForInstance` in class `AbstractClassifier`
      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 `AbstractClassifier`
      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]