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## weka.classifiers.meta
Class MultiBoostAB

    java.lang.Object
      weka.classifiers.Classifier
          weka.classifiers.SingleClassifierEnhancer
              weka.classifiers.IteratedSingleClassifierEnhancer
                  weka.classifiers.RandomizableIteratedSingleClassifierEnhancer
                      weka.classifiers.meta.AdaBoostM1
                          weka.classifiers.meta.MultiBoostAB

All Implemented Interfaces:
  java.io.Serializable, java.lang.Cloneable, Sourcable, OptionHandler, Randomizable, WeightedInstancesHandler

    public class MultiBoostAB

extends AdaBoostM1

Class for boosting a classifier using the MultiBoosting method.
MultiBoosting is an extension to the highly successful AdaBoost technique for forming decision committees. MultiBoosting can be viewed as combining AdaBoost with wagging. It is able to harness both AdaBoost's high bias and variance reduction with wagging's superior variance reduction. Using C4.5 as the base learning algorithm, Multi-boosting is demonstrated to produce decision committees with lower error than either AdaBoost or wagging significantly more often than the reverse over a large representative cross-section of UCI data sets. It offers the further advantage over AdaBoost of suiting parallel execution.
For more information, see

Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning, 40(2): 159-196, Kluwer Academic Publishers, Boston
Valid options are:

-D
Turn on debugging output.

-W classname
Specify the full class name of a classifier as the basis for boosting (required).

-I num
Set the number of boost iterations (default 10).

-P num
Set the percentage of weight mass used to build classifiers (default 100).

-Q
Use resampling instead of reweighting.

-S seed
Random number seed for resampling (default 1).

-C subcommittees
Number of sub-committees. (Default 3),

Options after -- are passed to the designated classifier.

Version:
  $Revision: 1.6.2.5 $ `
Author:
  Shane Butler (sbutle@deakin.edu.au), Eibe Frank (eibe@cs.waikato.ac.nz), Len Trigg (trigg@cs.waikato.ac.nz)
See Also:
  Serialized Form

Constructor Summary
`MultiBoostAB()`

Method Summary
`void` | `buildClassifier(Instances training)` Method for building this classifier.
`int` | `getNumSubCmtys()` Get the number of sub committees to use
`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` | `numSubCmtysTipText()` Returns the tip text for this property
`void` | `setNumSubCmtys(int subc)` Set the number of sub committees to use
`void` | `setOptions(java.lang.String[] options)` Parses a given list of options.
`java.lang.String` | `toString()` Returns description of the boosted classifier.

Methods inherited from class weka.classifiers.meta.AdaBoostM1
`distributionForInstance, getUseResampling, getWeightThreshold, setUseResampling, setWeightThreshold, toSource, useResamplingTipText, weightThresholdTipText`

Methods inherited from class weka.classifiers.RandomizableIteratedSingleClassifierEnhancer
`getSeed, seedTipText, setSeed`

Methods inherited from class weka.classifiers.IteratedSingleClassifierEnhancer
`getNumIterations, numIterationsTipText, setNumIterations`

Methods inherited from class weka.classifiers.SingleClassifierEnhancer
`classifierTipText, getClassifier, setClassifier`

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

### MultiBoostAB

    public MultiBoostAB()

Method Detail

### globalInfo

    public java.lang.String globalInfo()

  Returns a string describing classifier

  Overrides:
    `globalInfo` in class `AdaBoostM1`
  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 `AdaBoostM1`
  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:

  -D
  Turn on debugging output.

  -W classname
  Specify the full class name of a classifier as the basis for boosting (required).

  -I num
  Set the number of boost iterations (default 10).

  -P num
  Set the percentage of weight mass used to build classifiers (default 100).

  -Q
  Use resampling instead of reweighting.

  -S seed
  Random number seed for resampling (default 1).

  -C subcommittees
  Number of sub-committees. (Default 3),

  Options after -- are passed to the designated classifier.

  Specified by:
    `setOptions` in interface `OptionHandler`
  Overrides:
    `setOptions` in class `AdaBoostM1`
  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 `AdaBoostM1`
  Returns:
    an array of strings suitable for passing to setOptions

### numSubCmtysTipText

    public java.lang.String numSubCmtysTipText()

  Returns the tip text for this property

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

### setNumSubCmtys

    public void setNumSubCmtys(int subc)

  Set the number of sub committees to use

  Parameters:
    `seed` - the seed for resampling

### getNumSubCmtys

    public int getNumSubCmtys()

  Get the number of sub committees to use

  Returns:
    the seed for resampling

### buildClassifier

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

  Method for building this classifier.

  Overrides:
    `buildClassifier` in class `AdaBoostM1`
  Parameters:
    `training` - the training data to be used for generating the boosted classifier.
  Throws:
    `java.lang.Exception` - if the classifier could not be built successfully

### toString

    public java.lang.String toString()

  Returns description of the boosted classifier.

  Overrides:
    `toString` in class `AdaBoostM1`
  Returns:
    description of the boosted classifier as a string

### main

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

  Main method for testing this class.

  Parameters:
    `argv` - the options

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