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java.lang.Objectweka.classifiers.trees.j48.SplitCriterion
weka.classifiers.trees.j48.EntropyBasedSplitCrit
weka.classifiers.trees.j48.InfoGainSplitCrit
public final class InfoGainSplitCrit
Class for computing the information gain for a given distribution.
Constructor Summary | |
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InfoGainSplitCrit()
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Method Summary | |
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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 |
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logFunc, newEnt, oldEnt, splitEnt |
Methods inherited from class weka.classifiers.trees.j48.SplitCriterion |
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splitCritValue, splitCritValue, splitCritValue |
Methods inherited from class java.lang.Object |
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equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Constructor Detail |
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public InfoGainSplitCrit()
Method Detail |
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public final double splitCritValue(Distribution bags)
splitCritValue
in class SplitCriterion
public final double splitCritValue(Distribution bags, double totalNoInst)
bags
- the distributiontotalNoInst
- weight of ALL instances (including the
ones with missing values).public final double splitCritValue(Distribution bags, double totalNoInst, double oldEnt)
bags
- the distributiontotalNoInst
- weight of ALL instancesoldEnt
- entropy with respect to "no-split"-model.public java.lang.String getRevision()
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