MOA 12.03
Real Time Analytics for Data Streams
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Interface for computing splitting criteria. More...
Public Member Functions | |
double | getMeritOfSplit (double[] preSplitDist, double[][] postSplitDists) |
Computes the merit of splitting for a given ditribution before the split and after it. | |
double | getRangeOfMerit (double[] preSplitDist) |
Computes the range of splitting merit. |
Interface for computing splitting criteria.
with respect to distributions of class values. The split criterion is used as a parameter on decision trees and decision stumps. The two split criteria most used are Information Gain and Gini.
Definition at line 35 of file SplitCriterion.java.
double moa.classifiers.core.splitcriteria.SplitCriterion.getMeritOfSplit | ( | double[] | preSplitDist, |
double | postSplitDists[][] | ||
) |
Computes the merit of splitting for a given ditribution before the split and after it.
preSplitDist | the class distribution before the split |
postSplitDist | the class distribution after the split |
Implemented in moa.classifiers.core.splitcriteria.GiniSplitCriterion, and moa.classifiers.core.splitcriteria.InfoGainSplitCriterion.
Referenced by moa.classifiers.core.attributeclassobservers.VFMLNumericAttributeClassObserver.getBestEvaluatedSplitSuggestion(), moa.classifiers.core.attributeclassobservers.NominalAttributeClassObserver.getBestEvaluatedSplitSuggestion(), moa.classifiers.core.attributeclassobservers.GreenwaldKhannaNumericAttributeClassObserver.getBestEvaluatedSplitSuggestion(), moa.classifiers.core.attributeclassobservers.GaussianNumericAttributeClassObserver.getBestEvaluatedSplitSuggestion(), and moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserver.searchForBestSplitOption().
double moa.classifiers.core.splitcriteria.SplitCriterion.getRangeOfMerit | ( | double[] | preSplitDist | ) |
Computes the range of splitting merit.
preSplitDist | the class distribution before the split |
Implemented in moa.classifiers.core.splitcriteria.GiniSplitCriterion, and moa.classifiers.core.splitcriteria.InfoGainSplitCriterion.
Referenced by moa.classifiers.trees.HoeffdingTree.attemptToSplit(), and moa.classifiers.trees.HoeffdingOptionTree.attemptToSplit().