weka.classifiers.rules
Class M5Rules

java.lang.Object
  extended by weka.classifiers.AbstractClassifier
      extended by weka.classifiers.trees.m5.M5Base
          extended by weka.classifiers.rules.M5Rules
All Implemented Interfaces:
java.io.Serializable, java.lang.Cloneable, Classifier, AdditionalMeasureProducer, CapabilitiesHandler, 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: 1.11 $
Author:
Mark Hall
See Also:
Serialized Form

Constructor Summary
M5Rules()
          Constructor
 
Method Summary
 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
static void main(java.lang.String[] args)
          Main method by which this class can be tested
 
Methods inherited from class weka.classifiers.trees.m5.M5Base
buildClassifier, buildRegressionTreeTipText, classifyInstance, enumerateMeasures, generateRulesTipText, getBuildRegressionTree, getCapabilities, getM5RootNode, getMeasure, getMinNumInstances, getOptions, getUnpruned, getUseUnsmoothed, listOptions, measureNumRules, minNumInstancesTipText, setBuildRegressionTree, setMinNumInstances, setOptions, setUnpruned, setUseUnsmoothed, toString, unprunedTipText, useUnsmoothedTipText
 
Methods inherited from class weka.classifiers.AbstractClassifier
debugTipText, distributionForInstance, forName, getDebug, makeCopies, makeCopy, setDebug
 
Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait
 

Constructor Detail

M5Rules

public M5Rules()
Constructor

Method Detail

globalInfo

public java.lang.String globalInfo()
Returns a string describing classifier

Overrides:
globalInfo in class M5Base
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
Overrides:
getTechnicalInformation in class M5Base
Returns:
the technical information about this class

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[] args)
Main method by which this class can be tested

Parameters:
args - an array of options