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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 an model tree using M5 and makes the "best" leaf into a rule. Reference:
M. Hall, G. Holmes, E. Frank (1999). "Generating Rule Sets from Model Trees". Proceedings of the Twelfth Australian Joint Conference on Artificial Intelligence, Sydney, Australia. Springer-Verlag, pp. 1-12.Valid options are:
-U
Use unsmoothed predictions.
-R
Build regression tree/rule rather than model tree/rule
-M num
Minimum number of objects per leaf.
-N
Turns pruning off.
Constructor Summary | |
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M5Rules()
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Method Summary | |
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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, classifyInstance, enumerateMeasures, getBuildRegressionTree, getM5RootNode, getMeasure, getMinNumInstances, getOptions, getUnpruned, getUseUnsmoothed, listOptions, measureNumRules, setBuildRegressionTree, setMinNumInstances, setOptions, setUnpruned, setUseUnsmoothed, toString |
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 static void main(java.lang.String[] args)
args
- an array of options
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