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Class weka.classifiers.j48.BinC45ModelSelection 

java.lang.Object
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   +----weka.classifiers.j48.ModelSelection
           |
           +----weka.classifiers.j48.BinC45ModelSelection
public class BinC45ModelSelection
extends ModelSelection
Class for selecting a C4.5-like binary (!) split for a given dataset.

Version:
$Revision: 1.3 $
Author:
Eibe Frank (eibe@cs.waikato.ac.nz)

Constructor Index

o BinC45ModelSelection(int, Instances)
Initializes the split selection method with the given parameters.

Method Index

o cleanup()
Sets reference to training data to null.
o selectModel(Instances)
Selects C4.5-type split for the given dataset.
o selectModel(Instances, Instances)
Selects C4.5-type split for the given dataset.

Constructors

o BinC45ModelSelection 
 public BinC45ModelSelection(int m_minNoObj,
                             Instances allData)
Initializes the split selection method with the given parameters.

Parameters:
m_minNoObj - minimum number of instances that have to occur in at least two subsets induced by split
allData - FULL training dataset (necessary for selection of split points).

Methods

o cleanup 
 public void cleanup()
Sets reference to training data to null.

o selectModel 
 public final ClassifierSplitModel selectModel(Instances data)
Selects C4.5-type split for the given dataset.

Overrides:
selectModel in class ModelSelection
o selectModel 
 public final ClassifierSplitModel selectModel(Instances train,
                                               Instances test)
Selects C4.5-type split for the given dataset.

Overrides:
selectModel in class ModelSelection 
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