weka.classifiers.rules

Class M5Rules

java.lang.Object

weka.classifiers.AbstractClassifier

weka.classifiers.trees.m5.M5Base

weka.classifiers.rules.M5Rules

All Implemented Interfaces:

java.io.Serializable, java.lang.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: 8034 $

Author:

Mark Hall

See Also:

Serialized Form

Field Summary

Fields inherited from class weka.classifiers.AbstractClassifier

BATCH_SIZE_DEFAULT, NUM_DECIMAL_PLACES_DEFAULT

Constructor Summary

Constructors

Constructor and Description
M5Rules() Constructor

Method Summary

Modifier and Type	Method and Description
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

batchSizeTipText, debugTipText, distributionForInstance, distributionsForInstances, doNotCheckCapabilitiesTipText, forName, getBatchSize, getDebug, getDoNotCheckCapabilities, getNumDecimalPlaces, implementsMoreEfficientBatchPrediction, makeCopies, makeCopy, numDecimalPlacesTipText, postExecution, preExecution, run, runClassifier, setBatchSize, setDebug, setDoNotCheckCapabilities, setNumDecimalPlaces

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface weka.core.OptionHandler

makeCopy

Constructor Detail

M5Rules

public M5Rules()

Constructor

Method Detail

globalInfo

public java.lang.String globalInfo()

Returns a string describing classifier

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