weka.classifiers.bayes

Class NaiveBayesMultinomialUpdateable

java.lang.Object

weka.classifiers.Classifier

weka.classifiers.bayes.NaiveBayesMultinomial

weka.classifiers.bayes.NaiveBayesMultinomialUpdateable

All Implemented Interfaces:

java.io.Serializable, java.lang.Cloneable, UpdateableClassifier, CapabilitiesHandler, OptionHandler, RevisionHandler, TechnicalInformationHandler, WeightedInstancesHandler

public class NaiveBayesMultinomialUpdateable
extends NaiveBayesMultinomial
implements UpdateableClassifier

Class for building and using a multinomial Naive Bayes classifier. For more information see,

Andrew Mccallum, Kamal Nigam: A Comparison of Event Models for Naive Bayes Text Classification. In: AAAI-98 Workshop on 'Learning for Text Categorization', 1998.

The core equation for this classifier:

P[Ci|D] = (P[D|Ci] x P[Ci]) / P[D] (Bayes rule)

where Ci is class i and D is a document.

Incremental version of the algorithm.

BibTeX:

 @inproceedings{Mccallum1998,
    author = {Andrew Mccallum and Kamal Nigam},
    booktitle = {AAAI-98 Workshop on 'Learning for Text Categorization'},
    title = {A Comparison of Event Models for Naive Bayes Text Classification},
    year = {1998}
 }
 

Valid options are:

 -D
  If set, classifier is run in debug mode and
  may output additional info to the console

Version:

$Revision: 1.3 $

Author:

Andrew Golightly (acg4@cs.waikato.ac.nz), Bernhard Pfahringer (bernhard@cs.waikato.ac.nz), Jiang Su

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
NaiveBayesMultinomialUpdateable()

Method Summary

Modifier and Type	Method and Description
void	buildClassifier(Instances instances) Generates the classifier.
double[]	distributionForInstance(Instance instance) Calculates the class membership probabilities for the given test instance.
java.lang.String	getRevision() Returns the revision string.
java.lang.String	globalInfo() Returns a string describing this classifier
static void	main(java.lang.String[] args) Main method for testing this class.
java.lang.String	toString() Returns a string representation of the classifier.
void	updateClassifier(Instance instance) Updates the classifier with the given instance.

Methods inherited from class weka.classifiers.bayes.NaiveBayesMultinomial

getCapabilities, getTechnicalInformation, lnFactorial

Methods inherited from class weka.classifiers.Classifier

classifyInstance, debugTipText, forName, getDebug, getOptions, listOptions, makeCopies, makeCopy, setDebug, setOptions

Methods inherited from class java.lang.Object

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

Constructor Detail

NaiveBayesMultinomialUpdateable

public NaiveBayesMultinomialUpdateable()

Method Detail

globalInfo

public java.lang.String globalInfo()

Returns a string describing this classifier

Overrides:

globalInfo in class NaiveBayesMultinomial

Returns:

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

buildClassifier

public void buildClassifier(Instances instances)
                     throws java.lang.Exception

Generates the classifier.

Overrides:

buildClassifier in class NaiveBayesMultinomial

Parameters:

instances - set of instances serving as training data

Throws:

java.lang.Exception - if the classifier has not been generated successfully

updateClassifier

public void updateClassifier(Instance instance)
                      throws java.lang.Exception

Updates the classifier with the given instance.

Specified by:

updateClassifier in interface UpdateableClassifier

Parameters:

instance - the new training instance to include in the model

Throws:

java.lang.Exception - if the instance could not be incorporated in the model.

distributionForInstance

public double[] distributionForInstance(Instance instance)
                                 throws java.lang.Exception

Calculates the class membership probabilities for the given test instance.

Overrides:

distributionForInstance in class NaiveBayesMultinomial

Parameters:

instance - the instance to be classified

Returns:

predicted class probability distribution

Throws:

java.lang.Exception - if there is a problem generating the prediction

toString

public java.lang.String toString()

Returns a string representation of the classifier.

Overrides:

toString in class NaiveBayesMultinomial

Returns:

a string representation of the classifier

getRevision

public java.lang.String getRevision()

Returns the revision string.

Specified by:

getRevision in interface RevisionHandler

Overrides:

getRevision in class NaiveBayesMultinomial

Returns:

the revision

main

public static void main(java.lang.String[] args)

Main method for testing this class.

Parameters:

args - the options