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, CapabilitiesHandler, OptionHandler, RevisionHandler, TechnicalInformationHandler, WeightedInstancesHandler

public class NaiveBayesUpdateable
extends NaiveBayes
implements UpdateableClassifier

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:

 @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:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
NaiveBayesUpdateable()

Method Summary

Methods

Modifier and Type	Method and Description
String	getRevision() Returns the revision string.
TechnicalInformation	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.
String	globalInfo() Returns a string describing this classifier
static void	main(String[] argv) Main method for testing this class.
void	setUseSupervisedDiscretization(boolean newblah) Set whether supervised discretization is to be used.

Methods inherited from class weka.classifiers.bayes.NaiveBayes

buildClassifier, displayModelInOldFormatTipText, distributionForInstance, getCapabilities, getDisplayModelInOldFormat, getOptions, getUseKernelEstimator, getUseSupervisedDiscretization, listOptions, setDisplayModelInOldFormat, setOptions, setUseKernelEstimator, toString, updateClassifier, useKernelEstimatorTipText, useSupervisedDiscretizationTipText

Methods inherited from class weka.classifiers.AbstractClassifier

classifyInstance, debugTipText, forName, getDebug, makeCopies, makeCopy, runClassifier, setDebug

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface weka.classifiers.UpdateableClassifier

updateClassifier

Constructor Detail

NaiveBayesUpdateable

public NaiveBayesUpdateable()

Method Detail

globalInfo

public String globalInfo()

Returns a string describing this classifier

Overrides:

globalInfo in class NaiveBayes

Returns:

a description of the classifier suitable for displaying in the explorer/experimenter gui

getTechnicalInformation

public TechnicalInformation 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:

getTechnicalInformation in interface TechnicalInformationHandler

Overrides:

getTechnicalInformation in class NaiveBayes

Returns:

the technical information about this class

setUseSupervisedDiscretization

public void setUseSupervisedDiscretization(boolean newblah)

Set whether supervised discretization is to be used.

Overrides:

setUseSupervisedDiscretization in class NaiveBayes

Parameters:

newblah - true if supervised discretization is to be used.

getRevision

public String getRevision()

Returns the revision string.

Specified by:

getRevision in interface RevisionHandler

Overrides:

getRevision in class NaiveBayes

Returns:

the revision

main

public static void main(String[] argv)

Main method for testing this class.

Parameters:

argv - the options