Class BinC45ModelSelection
- java.lang.Object
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- org.processmining.plugins.workshop.Yaguang.WekaDiscriminationTree.ModelSelection
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- org.processmining.plugins.workshop.Yaguang.WekaDiscriminationTree.BinC45ModelSelection
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- All Implemented Interfaces:
java.io.Serializable
public class BinC45ModelSelection extends ModelSelection
Class for selecting a C4.5-like binary (!) split for a given dataset.- Version:
- $Revision: 1.8 $
- Author:
- Eibe Frank (eibe@cs.waikato.ac.nz)
- See Also:
- Serialized Form
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Field Summary
Fields Modifier and Type Field Description static BinC45SplitdiscModel
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Constructor Summary
Constructors Constructor Description BinC45ModelSelection(int minNoObj, Instances allData)Initializes the split selection method with the given parameters.
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description voidcleanup()Sets reference to training data to null.ClassifierSplitModelselectModel(Instances data)Selects C4.5-type split for the given dataset.ClassifierSplitModelselectModel(Instances train, Instances test)Selects C4.5-type split for the given dataset.
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Field Detail
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discModel
public static BinC45Split discModel
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Constructor Detail
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BinC45ModelSelection
public BinC45ModelSelection(int minNoObj, Instances allData)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).
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Method Detail
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cleanup
public void cleanup()
Sets reference to training data to null.
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selectModel
public final ClassifierSplitModel selectModel(Instances data)
Selects C4.5-type split for the given dataset.- Specified by:
selectModelin classModelSelection
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selectModel
public final ClassifierSplitModel selectModel(Instances train, Instances test)
Selects C4.5-type split for the given dataset.- Overrides:
selectModelin classModelSelection
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