weka.classifiers.bayes

Class NaiveBayesSimple

java.lang.Object

weka.classifiers.Classifier

weka.classifiers.bayes.NaiveBayesSimple

All Implemented Interfaces:

Serializable, Cloneable, CapabilitiesHandler, OptionHandler, RevisionHandler, TechnicalInformationHandler

public class NaiveBayesSimple
extends Classifier
implements 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: 5516 $

Author:

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

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
protected double[][][]	m_Counts All the counts for nominal attributes.
protected double[][]	m_Devs The standard deviations for numeric attributes.
protected Instances	m_Instances The instances used for training.
protected double[][]	m_Means The means for numeric attributes.
protected double[]	m_Priors The prior probabilities of the classes.
protected static double	NORM_CONST Constant for normal distribution.

Fields inherited from class weka.classifiers.Classifier

m_Debug

Constructor Summary

Constructors

Constructor and Description
NaiveBayesSimple()

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.
Capabilities	getCapabilities() Returns default capabilities of the classifier.
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.
protected double	normalDens(double x, double mean, double stdDev) Density function of normal distribution.
String	toString() Returns a description of the classifier.

Methods inherited from class weka.classifiers.Classifier

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

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Detail

m_Counts

protected double[][][] m_Counts

All the counts for nominal attributes.

m_Means

protected double[][] m_Means

The means for numeric attributes.

m_Devs

protected double[][] m_Devs

The standard deviations for numeric attributes.

m_Priors

protected double[] m_Priors

The prior probabilities of the classes.

m_Instances

protected Instances m_Instances

The instances used for training.

NORM_CONST

protected static double NORM_CONST

Constant for normal distribution.

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 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

Returns:

the technical information about this class

getCapabilities

public Capabilities getCapabilities()

Returns default capabilities of the classifier.

Specified by:

getCapabilities in interface CapabilitiesHandler

Overrides:

getCapabilities in class Classifier

Returns:

the capabilities of this classifier

See Also:

Capabilities

buildClassifier

public void buildClassifier(Instances instances)
                     throws Exception

Generates the classifier.

Specified by:

buildClassifier in class Classifier

Parameters:

instances - set of instances serving as training data

Throws:

Exception - if the classifier has not been generated successfully

distributionForInstance

public double[] distributionForInstance(Instance instance)
                                 throws Exception

Calculates the class membership probabilities for the given test instance.

Overrides:

distributionForInstance in class Classifier

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.

normalDens

protected double normalDens(double x,
                            double mean,
                            double stdDev)

Density function of normal distribution.

Parameters:

x - the value to get the density for

mean - the mean

stdDev - the standard deviation

Returns:

the density

getRevision

public String getRevision()

Returns the revision string.

Specified by:

getRevision in interface RevisionHandler

Overrides:

getRevision in class Classifier

Returns:

the revision

main

public static void main(String[] argv)

Main method for testing this class.

Parameters:

argv - the options