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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 | |
|---|---|
InfoGainSplitCrit()
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| Method Summary | |
|---|---|
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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