Class SimpleEstimator
- java.lang.Object
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- weka.classifiers.bayes.net.estimate.BayesNetEstimator
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- weka.classifiers.bayes.net.estimate.SimpleEstimator
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- All Implemented Interfaces:
java.io.Serializable
,OptionHandler
,RevisionHandler
- Direct Known Subclasses:
BMAEstimator
public class SimpleEstimator extends BayesNetEstimator
SimpleEstimator is used for estimating the conditional probability tables of a Bayes network once the structure has been learned. Estimates probabilities directly from data. Valid options are:-A <alpha> Initial count (alpha)
- Version:
- $Revision: 1.6 $
- Author:
- Remco Bouckaert (rrb@xm.co.nz)
- See Also:
- Serialized Form
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Constructor Summary
Constructors Constructor Description SimpleEstimator()
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description double[]
distributionForInstance(BayesNet bayesNet, Instance instance)
Calculates the class membership probabilities for the given test instance.void
estimateCPTs(BayesNet bayesNet)
estimateCPTs estimates the conditional probability tables for the Bayes Net using the network structure.java.lang.String
getRevision()
Returns the revision string.java.lang.String
globalInfo()
Returns a string describing this objectvoid
initCPTs(BayesNet bayesNet)
initCPTs reserves space for CPTs and set all counts to zerovoid
updateClassifier(BayesNet bayesNet, Instance instance)
Updates the classifier with the given instance.-
Methods inherited from class weka.classifiers.bayes.net.estimate.BayesNetEstimator
alphaTipText, getAlpha, getOptions, listOptions, setAlpha, setOptions
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Method Detail
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globalInfo
public java.lang.String globalInfo()
Returns a string describing this object- Overrides:
globalInfo
in classBayesNetEstimator
- Returns:
- a description of the classifier suitable for displaying in the explorer/experimenter gui
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estimateCPTs
public void estimateCPTs(BayesNet bayesNet) throws java.lang.Exception
estimateCPTs estimates the conditional probability tables for the Bayes Net using the network structure.- Overrides:
estimateCPTs
in classBayesNetEstimator
- Parameters:
bayesNet
- the bayes net to use- Throws:
java.lang.Exception
- if something goes wrong
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updateClassifier
public void updateClassifier(BayesNet bayesNet, Instance instance) throws java.lang.Exception
Updates the classifier with the given instance.- Overrides:
updateClassifier
in classBayesNetEstimator
- Parameters:
bayesNet
- the bayes net to useinstance
- the new training instance to include in the model- Throws:
java.lang.Exception
- if the instance could not be incorporated in the model.
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initCPTs
public void initCPTs(BayesNet bayesNet) throws java.lang.Exception
initCPTs reserves space for CPTs and set all counts to zero- Overrides:
initCPTs
in classBayesNetEstimator
- Parameters:
bayesNet
- the bayes net to use- Throws:
java.lang.Exception
- if something goes wrong
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distributionForInstance
public double[] distributionForInstance(BayesNet bayesNet, Instance instance) throws java.lang.Exception
Calculates the class membership probabilities for the given test instance.- Overrides:
distributionForInstance
in classBayesNetEstimator
- Parameters:
bayesNet
- the bayes net to useinstance
- the instance to be classified- Returns:
- predicted class probability distribution
- Throws:
java.lang.Exception
- if there is a problem generating the prediction
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getRevision
public java.lang.String getRevision()
Returns the revision string.- Specified by:
getRevision
in interfaceRevisionHandler
- Overrides:
getRevision
in classBayesNetEstimator
- Returns:
- the revision
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