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java.lang.Objectweka.classifiers.Classifier
weka.classifiers.trees.m5.M5Base
weka.classifiers.rules.M5Rules
public class M5Rules
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.
@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)
Constructor Summary | |
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M5Rules()
Constructor |
Method Summary | |
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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 |
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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.Classifier |
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debugTipText, distributionForInstance, forName, getDebug, makeCopies, makeCopy, setDebug |
Methods inherited from class java.lang.Object |
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equals, getClass, hashCode, notify, notifyAll, wait, wait, wait |
Constructor Detail |
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public M5Rules()
Method Detail |
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public java.lang.String globalInfo()
globalInfo
in class M5Base
public TechnicalInformation getTechnicalInformation()
getTechnicalInformation
in interface TechnicalInformationHandler
getTechnicalInformation
in class M5Base
public java.lang.String getRevision()
getRevision
in interface RevisionHandler
getRevision
in class Classifier
public static void main(java.lang.String[] args)
args
- an array of options
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