Package weka.classifiers.meta

Class RandomCommittee

  • All Implemented Interfaces:
    Serializable, Cloneable, Classifier, BatchPredictor, CapabilitiesHandler, CapabilitiesIgnorer, CommandlineRunnable, OptionHandler, PartitionGenerator, Randomizable, RevisionHandler, WeightedInstancesHandler
    public class RandomCommittee
extends RandomizableParallelIteratedSingleClassifierEnhancer
implements WeightedInstancesHandler, PartitionGenerator
    Class for building an ensemble of randomizable base classifiers. Each base classifiers is built using a different random number seed (but based one the same data). The final prediction is a straight average of the predictions generated by the individual base classifiers.

    Valid options are: 

     -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.RandomTree)
     
 Options specific to classifier weka.classifiers.trees.RandomTree:
 
     -K <number of attributes>
  Number of attributes to randomly investigate
  (<1 = int(log(#attributes)+1)).
     -M <minimum number of instances>
  Set minimum number of instances per leaf.
     -S <num>
  Seed for random number generator.
  (default 1)
     -depth <num>
  The maximum depth of the tree, 0 for unlimited.
  (default 0)
     -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.

    Version:
    $Revision$
    Author:
    Eibe Frank (eibe@cs.waikato.ac.nz)
    See Also:
    Serialized Form