Package weka.classifiers.rules

Class M5Rules

  • All Implemented Interfaces:
    Serializable, Cloneable, Classifier, AdditionalMeasureProducer, BatchPredictor, CapabilitiesHandler, CapabilitiesIgnorer, CommandlineRunnable, OptionHandler, RevisionHandler, TechnicalInformationHandler
    public class M5Rules
extends M5Base
implements TechnicalInformationHandler
    Generates a decision list for regression problems using separate-and-conquer. In each iteration it builds a model tree using M5 and makes the "best" leaf into a rule.

    For more information see:

    Geoffrey Holmes, Mark Hall, Eibe Frank: Generating Rule Sets from Model Trees. In: Twelfth Australian Joint Conference on Artificial Intelligence, 1-12, 1999.

    Ross J. Quinlan: Learning with Continuous Classes. In: 5th Australian Joint Conference on Artificial Intelligence, Singapore, 343-348, 1992.

    Y. Wang, I. H. Witten: Induction of model trees for predicting continuous classes. In: Poster papers of the 9th European Conference on Machine Learning, 1997.

    BibTeX: 

     @inproceedings{Holmes1999,
    author = {Geoffrey Holmes and Mark Hall and Eibe Frank},
    booktitle = {Twelfth Australian Joint Conference on Artificial Intelligence},
    pages = {1-12},
    publisher = {Springer},
    title = {Generating Rule Sets from Model Trees},
    year = {1999}
 }
 
 @inproceedings{Quinlan1992,
    address = {Singapore},
    author = {Ross J. Quinlan},
    booktitle = {5th Australian Joint Conference on Artificial Intelligence},
    pages = {343-348},
    publisher = {World Scientific},
    title = {Learning with Continuous Classes},
    year = {1992}
 }
 
 @inproceedings{Wang1997,
    author = {Y. Wang and I. H. Witten},
    booktitle = {Poster papers of the 9th European Conference on Machine Learning},
    publisher = {Springer},
    title = {Induction of model trees for predicting continuous classes},
    year = {1997}
 }

    Valid options are: 

     -N
  Use unpruned tree/rules
     -U
  Use unsmoothed predictions
     -R
  Build regression tree/rule rather than a model tree/rule
     -M <minimum number of instances>
  Set minimum number of instances per leaf
  (default 4)
    Version:
    $Revision$
    Author:
    Mark Hall
    See Also:
    Serialized Form

    • Constructor Detail

      • M5Rules

        public M5Rules()
        Constructor

    • Method Detail

      • globalInfo

        public String globalInfo()
        Returns a string describing classifier
        Returns:
        a description suitable for displaying in the explorer/experimenter gui

      • main

        public static void main​(String[] args)
        Main method by which this class can be tested
        Parameters:
        args - an array of options