类 MultiBoostAB

所有已实现的接口:
Serializable, Cloneable, Sourcable, CapabilitiesHandler, OptionHandler, Randomizable, RevisionHandler, TechnicalInformationHandler, WeightedInstancesHandler

public class MultiBoostAB extends AdaBoostM1 implements TechnicalInformationHandler
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. Vol.40(No.2).

BibTeX:

 @article{Webb2000,
    address = {Boston},
    author = {Geoffrey I. Webb},
    journal = {Machine Learning},
    number = {No.2},
    publisher = {Kluwer Academic Publishers},
    title = {MultiBoosting: A Technique for Combining Boosting and Wagging},
    volume = {Vol.40},
    year = {2000}
 }
 

Valid options are:

 -C <num>
  Number of sub-committees. (Default 3)
 -P <num>
  Percentage of weight mass to base training on.
  (default 100, reduce to around 90 speed up)
 -Q
  Use resampling for boosting.
 -S <num>
  Random number seed.
  (default 1)
 -I <num>
  Number of iterations.
  (default 10)
 -D
  If set, classifier is run in debug mode and
  may output additional info to the console
 -W
  Full name of base classifier.
  (default: weka.classifiers.trees.DecisionStump)
 
 Options specific to classifier weka.classifiers.trees.DecisionStump:
 
 -D
  If set, classifier is run in debug mode and
  may output additional info to the console
Options after -- are passed to the designated classifier.

版本:
$Revision: 1.16 $
作者:
Shane Butler (sbutle@deakin.edu.au), Eibe Frank (eibe@cs.waikato.ac.nz), Len Trigg (trigg@cs.waikato.ac.nz)
另请参阅:
  • 构造器详细资料

    • MultiBoostAB

      public MultiBoostAB()
  • 方法详细资料

    • globalInfo

      public String globalInfo()
      Returns a string describing classifier
      覆盖:
      globalInfo 在类中 AdaBoostM1
      返回:
      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.
      指定者:
      getTechnicalInformation 在接口中 TechnicalInformationHandler
      覆盖:
      getTechnicalInformation 在类中 AdaBoostM1
      返回:
      the technical information about this class
    • listOptions

      public Enumeration listOptions()
      Returns an enumeration describing the available options
      指定者:
      listOptions 在接口中 OptionHandler
      覆盖:
      listOptions 在类中 AdaBoostM1
      返回:
      an enumeration of all the available options
    • setOptions

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

      Valid options are:

       -C <num>
        Number of sub-committees. (Default 3)
       -P <num>
        Percentage of weight mass to base training on.
        (default 100, reduce to around 90 speed up)
       -Q
        Use resampling for boosting.
       -S <num>
        Random number seed.
        (default 1)
       -I <num>
        Number of iterations.
        (default 10)
       -D
        If set, classifier is run in debug mode and
        may output additional info to the console
       -W
        Full name of base classifier.
        (default: weka.classifiers.trees.DecisionStump)
       
       Options specific to classifier weka.classifiers.trees.DecisionStump:
       
       -D
        If set, classifier is run in debug mode and
        may output additional info to the console
      Options after -- are passed to the designated classifier.

      指定者:
      setOptions 在接口中 OptionHandler
      覆盖:
      setOptions 在类中 AdaBoostM1
      参数:
      options - the list of options as an array of strings
      抛出:
      Exception - if an option is not supported
    • getOptions

      public String[] getOptions()
      Gets the current settings of the Classifier.
      指定者:
      getOptions 在接口中 OptionHandler
      覆盖:
      getOptions 在类中 AdaBoostM1
      返回:
      an array of strings suitable for passing to setOptions
    • numSubCmtysTipText

      public String numSubCmtysTipText()
      Returns the tip text for this property
      返回:
      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
      参数:
      subc - the number of sub committees
    • getNumSubCmtys

      public int getNumSubCmtys()
      Get the number of sub committees to use
      返回:
      the seed for resampling
    • buildClassifier

      public void buildClassifier(Instances training) throws Exception
      Method for building this classifier.
      覆盖:
      buildClassifier 在类中 AdaBoostM1
      参数:
      training - the data to train with
      抛出:
      Exception - if the training fails
    • toString

      public String toString()
      Returns description of the boosted classifier.
      覆盖:
      toString 在类中 AdaBoostM1
      返回:
      description of the boosted classifier as a string
    • getRevision

      public String getRevision()
      Returns the revision string.
      指定者:
      getRevision 在接口中 RevisionHandler
      覆盖:
      getRevision 在类中 AdaBoostM1
      返回:
      the revision
    • main

      public static void main(String[] argv)
      Main method for testing this class.
      参数:
      argv - the options