Package weka.classifiers.trees.ht
Class NBNode
java.lang.Object
weka.classifiers.trees.ht.HNode
weka.classifiers.trees.ht.LeafNode
weka.classifiers.trees.ht.ActiveHNode
weka.classifiers.trees.ht.NBNode
- All Implemented Interfaces:
Serializable
,LearningNode
- Direct Known Subclasses:
NBNodeAdaptive
Implements a LearningNode that uses a naive Bayes model
- Version:
- $Revision: 9705 $
- Author:
- Richard Kirkby (rkirkby@cs.waikato.ac.nz), Mark Hall (mhall{[at]}pentaho{[dot]}com)
- See Also:
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Field Summary
Fields inherited from class weka.classifiers.trees.ht.ActiveHNode
m_weightSeenAtLastSplitEval
Fields inherited from class weka.classifiers.trees.ht.LeafNode
m_parentBranch, m_parentNode, m_theNode
Fields inherited from class weka.classifiers.trees.ht.HNode
m_classDistribution
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Constructor Summary
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Method Summary
Modifier and TypeMethodDescriptiondouble[]
getDistribution
(Instance inst, Attribute classAtt) Return a class probability distribution computed from the frequency counts at this nodevoid
updateNode
(Instance inst) Update the node with the supplied instanceMethods inherited from class weka.classifiers.trees.ht.ActiveHNode
getPossibleSplits
Methods inherited from class weka.classifiers.trees.ht.HNode
classDistributionIsPure, graphTree, installNodeNums, isLeaf, leafForInstance, numEntriesInClassDistribution, toString, totalWeight, updateDistribution
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Constructor Details
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NBNode
Construct a new NBNode- Parameters:
header
- the instances structure of the data we're learning fromnbWeightThreshold
- the weight mass to see before allowing naive Bayes to predict- Throws:
Exception
- if a problem occurs
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Method Details
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updateNode
Description copied from class:HNode
Update the node with the supplied instance- Overrides:
updateNode
in classActiveHNode
- Parameters:
inst
- the instance to update with- Throws:
Exception
- if a problem occurs
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getDistribution
Description copied from class:HNode
Return a class probability distribution computed from the frequency counts at this node- Overrides:
getDistribution
in classHNode
- Parameters:
inst
- the instance to get a prediction forclassAtt
- the class attribute- Returns:
- a class probability distribution
- Throws:
Exception
- if a problem occurs
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