weka.classifiers.bayes
Class NaiveBayesSimple

java.lang.Object
  weka.classifiers.AbstractClassifier
      weka.classifiers.bayes.NaiveBayesSimple

All Implemented Interfaces:

Serializable, Cloneable, weka.classifiers.Classifier, weka.core.CapabilitiesHandler, weka.core.OptionHandler, weka.core.RevisionHandler, weka.core.TechnicalInformationHandler

public class NaiveBayesSimple
extends weka.classifiers.AbstractClassifier
implements weka.core.TechnicalInformationHandler

Class for building and using a simple Naive Bayes classifier.Numeric attributes are modelled by a normal distribution.

For more information, see

Richard Duda, Peter Hart (1973). Pattern Classification and Scene Analysis. Wiley, New York.

BibTeX:

 @book{Duda1973,
    address = {New York},
    author = {Richard Duda and Peter Hart},
    publisher = {Wiley},
    title = {Pattern Classification and Scene Analysis},
    year = {1973}
 }
 

Valid options are:

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

Version:

$Revision: 8109 $

Author:

Eibe Frank (eibe@cs.waikato.ac.nz)

See Also:

Serialized Form

Constructor Summary

NaiveBayesSimple()

Method Summary

void	buildClassifier(weka.core.Instances instances) Generates the classifier.
double[]	distributionForInstance(weka.core.Instance instance) Calculates the class membership probabilities for the given test instance.
weka.core.Capabilities	getCapabilities() Returns default capabilities of the classifier.
String	getRevision() Returns the revision string.
weka.core.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.
String	toString() Returns a description of the classifier.

Methods inherited from class weka.classifiers.AbstractClassifier

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

Methods inherited from class java.lang.Object

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

Constructor Detail

NaiveBayesSimple

public NaiveBayesSimple()

Method Detail

globalInfo

public String globalInfo()

Returns a string describing this classifier

Returns:

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

getTechnicalInformation

public weka.core.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 weka.core.TechnicalInformationHandler

Returns:

the technical information about this class

getCapabilities

public weka.core.Capabilities getCapabilities()

Returns default capabilities of the classifier.

Specified by:

getCapabilities in interface weka.classifiers.Classifier

Specified by:

getCapabilities in interface weka.core.CapabilitiesHandler

Overrides:

getCapabilities in class weka.classifiers.AbstractClassifier

Returns:

the capabilities of this classifier

buildClassifier

public void buildClassifier(weka.core.Instances instances)
                     throws Exception

Generates the classifier.

Specified by:

buildClassifier in interface weka.classifiers.Classifier

Parameters:

instances - set of instances serving as training data

Throws:

Exception - if the classifier has not been generated successfully

distributionForInstance

public double[] distributionForInstance(weka.core.Instance instance)
                                 throws Exception

Calculates the class membership probabilities for the given test instance.

Specified by:

distributionForInstance in interface weka.classifiers.Classifier

Overrides:

distributionForInstance in class weka.classifiers.AbstractClassifier

Parameters:

instance - the instance to be classified

Returns:

predicted class probability distribution

Throws:

Exception - if distribution can't be computed

toString

public String toString()

Returns a description of the classifier.

Overrides:

toString in class Object

Returns:

a description of the classifier as a string.

getRevision

public String getRevision()

Returns the revision string.

Specified by:

getRevision in interface weka.core.RevisionHandler

Overrides:

getRevision in class weka.classifiers.AbstractClassifier

Returns:

the revision

main

public static void main(String[] argv)

Main method for testing this class.

Parameters:

argv - the options