Package weka.classifiers.trees.j48
Class BinC45ModelSelection
java.lang.Object
weka.classifiers.trees.j48.ModelSelection
weka.classifiers.trees.j48.BinC45ModelSelection
- All Implemented Interfaces:
Serializable
,RevisionHandler
Class for selecting a C4.5-like binary (!) split for a given dataset.
- Version:
- $Revision: 10531 $
- Author:
- Eibe Frank (eibe@cs.waikato.ac.nz)
- See Also:
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Constructor Summary
ConstructorDescriptionBinC45ModelSelection
(int minNoObj, Instances allData, boolean useMDLcorrection, boolean doNotMakeSplitPointActualValue) Initializes the split selection method with the given parameters. -
Method Summary
Modifier and TypeMethodDescriptionvoid
cleanup()
Sets reference to training data to null.Returns the revision string.final ClassifierSplitModel
selectModel
(Instances data) Selects C4.5-type split for the given dataset.final ClassifierSplitModel
selectModel
(Instances train, Instances test) Selects C4.5-type split for the given dataset.
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Constructor Details
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BinC45ModelSelection
public BinC45ModelSelection(int minNoObj, Instances allData, boolean useMDLcorrection, boolean doNotMakeSplitPointActualValue) Initializes the split selection method with the given parameters.- Parameters:
minNoObj
- minimum number of instances that have to occur in at least two subsets induced by splitallData
- FULL training dataset (necessary for selection of split points).useMDLcorrection
- whether to use MDL adjustement when finding splits on numeric attributes
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Method Details
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cleanup
public void cleanup()Sets reference to training data to null. -
selectModel
Selects C4.5-type split for the given dataset.- Specified by:
selectModel
in classModelSelection
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selectModel
Selects C4.5-type split for the given dataset.- Overrides:
selectModel
in classModelSelection
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getRevision
Returns the revision string.- Returns:
- the revision
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