Class MultiNomialBMAEstimator
java.lang.Object
weka.classifiers.bayes.net.estimate.BayesNetEstimator
weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator
- All Implemented Interfaces:
Serializable
,OptionHandler
,RevisionHandler
Multinomial BMA Estimator.
Valid options are:
-k2 Whether to use K2 prior.
-A <alpha> Initial count (alpha)
- Version:
- $Revision: 12470 $
- Author:
- Remco Bouckaert (rrb@xm.co.nz)
- See Also:
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Constructor Summary
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Method Summary
Modifier and TypeMethodDescriptiondouble[]
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.String[]
Gets the current settings of the classifier.Returns the revision string.Returns a string describing this objectvoid
initCPTs reserves space for CPTs and set all counts to zeroboolean
Returns an enumeration describing the available optionsvoid
setOptions
(String[] options) Parses a given list of options.void
setUseK2Prior
(boolean bUseK2Prior) Sets the UseK2Prior.void
updateClassifier
(BayesNet bayesNet, Instance instance) Updates the classifier with the given instance.Methods inherited from class weka.classifiers.bayes.net.estimate.BayesNetEstimator
alphaTipText, getAlpha, setAlpha
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Constructor Details
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MultiNomialBMAEstimator
public MultiNomialBMAEstimator()
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Method Details
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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
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:
Exception
- if number of parents doesn't fit (more than 1)
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updateClassifier
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:
Exception
- if the instance could not be incorporated in the model.
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initCPTs
initCPTs reserves space for CPTs and set all counts to zero- Overrides:
initCPTs
in classBayesNetEstimator
- Parameters:
bayesNet
- the bayes net to use- Throws:
Exception
- doesn't apply
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isUseK2Prior
public boolean isUseK2Prior()- Returns:
- boolean
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setUseK2Prior
public void setUseK2Prior(boolean bUseK2Prior) Sets the UseK2Prior.- Parameters:
bUseK2Prior
- The bUseK2Prior to set
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distributionForInstance
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:
Exception
- if there is a problem generating the prediction
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listOptions
Returns an enumeration describing the available options- Specified by:
listOptions
in interfaceOptionHandler
- Overrides:
listOptions
in classBayesNetEstimator
- Returns:
- an enumeration of all the available options
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setOptions
Parses a given list of options. Valid options are:-k2 Whether to use K2 prior.
-A <alpha> Initial count (alpha)
- Specified by:
setOptions
in interfaceOptionHandler
- Overrides:
setOptions
in classBayesNetEstimator
- Parameters:
options
- the list of options as an array of strings- Throws:
Exception
- if an option is not supported
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getOptions
Gets the current settings of the classifier.- Specified by:
getOptions
in interfaceOptionHandler
- Overrides:
getOptions
in classBayesNetEstimator
- Returns:
- an array of strings suitable for passing to setOptions
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getRevision
Returns the revision string.- Specified by:
getRevision
in interfaceRevisionHandler
- Overrides:
getRevision
in classBayesNetEstimator
- Returns:
- the revision
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