weka.classifiers.rules
Class M5Rules
java.lang.Object
|
+--weka.classifiers.Classifier
|
+--weka.classifiers.trees.m5.M5Base
|
+--weka.classifiers.rules.M5Rules
- All Implemented Interfaces:
- AdditionalMeasureProducer, java.lang.Cloneable, OptionHandler, java.io.Serializable
- public class M5Rules
- extends M5Base
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:\n\n"
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
Minimum number of objects per leaf.
-N
Turns pruning off.
- Version:
- $Revision: 1.3 $
- Author:
- Mark Hall
- See Also:
- Serialized Form
Method Summary |
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, classifyInstance, enumerateMeasures, getBuildRegressionTree, getM5RootNode, getMeasure, getMinNumInstances, getOptions, getUnpruned, getUseUnsmoothed, listOptions, measureNumRules, setBuildRegressionTree, setMinNumInstances, setOptions, setUnpruned, setUseUnsmoothed, toString |
Methods inherited from class java.lang.Object |
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait |
M5Rules
public M5Rules()
globalInfo
public java.lang.String globalInfo()
- Returns a string describing classifier
- Returns:
- a description suitable for
displaying in the explorer/experimenter gui
main
public static void main(java.lang.String[] args)
- Main method by which this class can be tested
- Parameters:
args
- an array of options
Copyright (c)
2003 David Lindsay, Computer Learning Research Centre, Dept. Computer Science, Royal Holloway, University of London