Package weka.classifiers.trees.ht
Class ConditionalSufficientStats
java.lang.Object
weka.classifiers.trees.ht.ConditionalSufficientStats
- All Implemented Interfaces:
Serializable
- Direct Known Subclasses:
GaussianConditionalSufficientStats,NominalConditionalSufficientStats
Records sufficient stats for an attribute
- Version:
- $Revision: 9705 $
- Author:
- Richard Kirkby (rkirkby@cs.waikato.ac.nz), Mark Hall (mhall{[at]}pentaho{[dot]}com)
- See Also:
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Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptionabstract SplitCandidatebestSplit(SplitMetric splitMetric, Map<String, WeightMass> preSplitDist, String attName) Return the best splitabstract doubleprobabilityOfAttValConditionedOnClass(double attVal, String classVal) Return the probability of an attribute value conditioned on a class valueabstract voidUpdate this stat with the supplied attribute value and class value
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Constructor Details
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ConditionalSufficientStats
public ConditionalSufficientStats()
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Method Details
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update
Update this stat with the supplied attribute value and class value- Parameters:
attVal- the value of the attributeclassVal- the class valueweight- the weight of this observation
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probabilityOfAttValConditionedOnClass
Return the probability of an attribute value conditioned on a class value- Parameters:
attVal- the attribute value to compute the conditional probability forclassVal- the class value- Returns:
- the probability
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bestSplit
public abstract SplitCandidate bestSplit(SplitMetric splitMetric, Map<String, WeightMass> preSplitDist, String attName) Return the best split- Parameters:
splitMetric- the split metric to usepreSplitDist- the distribution of class values prior to splittingattName- the name of the attribute being considered for splitting- Returns:
- the best split for the attribute
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