Package weka.classifiers.trees.j48
Class InfoGainSplitCrit
- java.lang.Object
-
- weka.classifiers.trees.j48.SplitCriterion
-
- weka.classifiers.trees.j48.EntropyBasedSplitCrit
-
- weka.classifiers.trees.j48.InfoGainSplitCrit
-
- All Implemented Interfaces:
java.io.Serializable
,RevisionHandler
public final class InfoGainSplitCrit extends EntropyBasedSplitCrit
Class for computing the information gain for a given distribution.- Version:
- $Revision: 1.10 $
- Author:
- Eibe Frank (eibe@cs.waikato.ac.nz)
- See Also:
- Serialized Form
-
-
Constructor Summary
Constructors Constructor Description InfoGainSplitCrit()
-
Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description java.lang.String
getRevision()
Returns the revision string.double
splitCritValue(Distribution bags)
This method is a straightforward implementation of the information gain criterion for the given distribution.double
splitCritValue(Distribution bags, double totalNoInst)
This method computes the information gain in the same way C4.5 does.double
splitCritValue(Distribution bags, double totalNoInst, double oldEnt)
This method computes the information gain in the same way C4.5 does.-
Methods inherited from class weka.classifiers.trees.j48.EntropyBasedSplitCrit
logFunc, newEnt, oldEnt, splitEnt
-
Methods inherited from class weka.classifiers.trees.j48.SplitCriterion
splitCritValue, splitCritValue, splitCritValue
-
-
-
-
Method Detail
-
splitCritValue
public final double splitCritValue(Distribution bags)
This method is a straightforward implementation of the information gain criterion for the given distribution.- Overrides:
splitCritValue
in classSplitCriterion
- Returns:
- value of splitting criterion. 0 by default
-
splitCritValue
public final double splitCritValue(Distribution bags, double totalNoInst)
This method computes the information gain in the same way C4.5 does.- Parameters:
bags
- the distributiontotalNoInst
- weight of ALL instances (including the ones with missing values).
-
splitCritValue
public final double splitCritValue(Distribution bags, double totalNoInst, double oldEnt)
This method computes the information gain in the same way C4.5 does.- Parameters:
bags
- the distributiontotalNoInst
- weight of ALL instancesoldEnt
- entropy with respect to "no-split"-model.
-
getRevision
public java.lang.String getRevision()
Returns the revision string.- Returns:
- the revision
-
-