Package weka.classifiers.bayes
Class NaiveBayesUpdateable
java.lang.Object
weka.classifiers.AbstractClassifier
weka.classifiers.bayes.NaiveBayes
weka.classifiers.bayes.NaiveBayesUpdateable
- All Implemented Interfaces:
Serializable,Cloneable,Classifier,UpdateableClassifier,Aggregateable<NaiveBayes>,BatchPredictor,CapabilitiesHandler,CapabilitiesIgnorer,CommandlineRunnable,OptionHandler,RevisionHandler,TechnicalInformationHandler,WeightedAttributesHandler,WeightedInstancesHandler
Class for a Naive Bayes classifier using estimator classes. This is the updateable version of NaiveBayes.
This classifier will use a default precision of 0.1 for numeric attributes when buildClassifier is called with zero training instances.
For more information on Naive Bayes classifiers, see
George H. John, Pat Langley: Estimating Continuous Distributions in Bayesian Classifiers. In: Eleventh Conference on Uncertainty in Artificial Intelligence, San Mateo, 338-345, 1995. BibTeX:
This classifier will use a default precision of 0.1 for numeric attributes when buildClassifier is called with zero training instances.
For more information on Naive Bayes classifiers, see
George H. John, Pat Langley: Estimating Continuous Distributions in Bayesian Classifiers. In: Eleventh Conference on Uncertainty in Artificial Intelligence, San Mateo, 338-345, 1995. BibTeX:
@inproceedings{John1995,
address = {San Mateo},
author = {George H. John and Pat Langley},
booktitle = {Eleventh Conference on Uncertainty in Artificial Intelligence},
pages = {338-345},
publisher = {Morgan Kaufmann},
title = {Estimating Continuous Distributions in Bayesian Classifiers},
year = {1995}
}
Valid options are:
-K Use kernel density estimator rather than normal distribution for numeric attributes
-D Use supervised discretization to process numeric attributes
-O Display model in old format (good when there are many classes)
- Version:
- $Revision: 8034 $
- Author:
- Len Trigg (trigg@cs.waikato.ac.nz), Eibe Frank (eibe@cs.waikato.ac.nz)
- See Also:
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Field Summary
Fields inherited from class weka.classifiers.AbstractClassifier
BATCH_SIZE_DEFAULT, NUM_DECIMAL_PLACES_DEFAULT -
Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptionReturns the revision string.Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.Returns a string describing this classifierstatic voidMain method for testing this class.voidsetUseSupervisedDiscretization(boolean newblah) Set whether supervised discretization is to be used.Methods inherited from class weka.classifiers.bayes.NaiveBayes
aggregate, buildClassifier, displayModelInOldFormatTipText, distributionForInstance, finalizeAggregation, getCapabilities, getClassEstimator, getConditionalEstimators, getDisplayModelInOldFormat, getHeader, getOptions, getUseKernelEstimator, getUseSupervisedDiscretization, listOptions, setDisplayModelInOldFormat, setOptions, setUseKernelEstimator, toString, updateClassifier, useKernelEstimatorTipText, useSupervisedDiscretizationTipTextMethods inherited from class weka.classifiers.AbstractClassifier
batchSizeTipText, classifyInstance, debugTipText, distributionsForInstances, doNotCheckCapabilitiesTipText, forName, getBatchSize, getDebug, getDoNotCheckCapabilities, getNumDecimalPlaces, implementsMoreEfficientBatchPrediction, makeCopies, makeCopy, numDecimalPlacesTipText, postExecution, preExecution, run, runClassifier, setBatchSize, setDebug, setDoNotCheckCapabilities, setNumDecimalPlacesMethods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, wait, wait, waitMethods inherited from interface weka.classifiers.UpdateableClassifier
updateClassifier
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Constructor Details
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NaiveBayesUpdateable
public NaiveBayesUpdateable()
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Method Details
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globalInfo
Returns a string describing this classifier- Overrides:
globalInfoin classNaiveBayes- Returns:
- a description of the classifier suitable for displaying in the explorer/experimenter gui
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getTechnicalInformation
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.- Specified by:
getTechnicalInformationin interfaceTechnicalInformationHandler- Overrides:
getTechnicalInformationin classNaiveBayes- Returns:
- the technical information about this class
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setUseSupervisedDiscretization
public void setUseSupervisedDiscretization(boolean newblah) Set whether supervised discretization is to be used.- Overrides:
setUseSupervisedDiscretizationin classNaiveBayes- Parameters:
newblah- true if supervised discretization is to be used.
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getRevision
Returns the revision string.- Specified by:
getRevisionin interfaceRevisionHandler- Overrides:
getRevisionin classNaiveBayes- Returns:
- the revision
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main
Main method for testing this class.- Parameters:
argv- the options
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