Package weka.classifiers.trees.j48

Class C45ModelSelection

java.lang.Object

weka.classifiers.trees.j48.ModelSelection

weka.classifiers.trees.j48.C45ModelSelection

All Implemented Interfaces:

Serializable, RevisionHandler

public class C45ModelSelection
extends ModelSelection

Class for selecting a C4.5-type split for a given dataset.

Version:

$Revision: 15122 $

Author:

Eibe Frank (eibe@cs.waikato.ac.nz)

See Also:

• Serialized Form

Constructor Summary

Constructors

Constructor	Description
C45ModelSelection(int minNoObj, Instances allData, boolean useMDLcorrection, boolean doNotMakeSplitPointActualValue)	Initializes the split selection method with the given parameters.

Method Summary

Modifier and Type	Method	Description
void	cleanup()	Sets reference to training data to null.
String	getRevision()	Returns the revision string.
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.

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Details

C45ModelSelection

public C45ModelSelection(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 split

allData - FULL training dataset (necessary for selection of split points).

useMDLcorrection - whether to use MDL adjustement when finding splits on numeric attributes

doNotMakeSplitPointActualValue - if true, split point is not relocated by scanning the entire dataset for the closest data value

Method Details

cleanup

public void cleanup()

Sets reference to training data to null.

selectModel

public ClassifierSplitModel selectModel(Instances data)

Selects C4.5-type split for the given dataset.

Specified by:

selectModel in class ModelSelection

selectModel

public final ClassifierSplitModel selectModel(Instances train,
 Instances test)

Selects C4.5-type split for the given dataset.

Overrides:

selectModel in class ModelSelection

getRevision

public String getRevision()

Returns the revision string.

Returns:

the revision