weka.classifiers.bayes
Class NaiveBayesMultinomial

java.lang.Object
  weka.classifiers.Classifier
      weka.classifiers.bayes.NaiveBayesMultinomial

All Implemented Interfaces:

java.lang.Cloneable, OptionHandler, java.io.Serializable, WeightedInstancesHandler

public class NaiveBayesMultinomial

extends Classifier

implements WeightedInstancesHandler

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

See Also:

Serialized Form

Field Summary

(package private) Instances	headerInfo
private double[]	lnFactorialCache
private int	numAttributes
private int	numClasses
private double[]	probOfClass
private double[][]	probOfWordGivenClass

Fields inherited from class weka.classifiers.Classifier

m_Debug

Constructor Summary

NaiveBayesMultinomial()

Method Summary

void	buildClassifier(Instances instances) Generates the classifier.
double[]	distributionForInstance(Instance instance) Calculates the class membership probabilities for the given test instance.
java.lang.String	globalInfo() Returns a string describing this classifier
double	lnFactorial(int n) Fast computation of ln(n!)
static void	main(java.lang.String[] argv) Main method for testing this class.
private double	probOfDocGivenClass(Instance inst, int classIndex) log(N!)
java.lang.String	toString()

Methods inherited from class weka.classifiers.Classifier

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

Methods inherited from class java.lang.Object

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

Field Detail

probOfWordGivenClass

private double[][] probOfWordGivenClass

probOfClass

private double[] probOfClass

numAttributes

private int numAttributes

numClasses

private int numClasses

lnFactorialCache

private double[] lnFactorialCache

headerInfo

Instances headerInfo

Constructor Detail

NaiveBayesMultinomial

public NaiveBayesMultinomial()

Method Detail

globalInfo

public java.lang.String globalInfo()

Returns a string describing this classifier

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.

Specified by:

buildClassifier in class Classifier

Parameters:

instances - set of instances serving as training data

Throws:

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

distributionForInstance

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

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

probOfDocGivenClass

private double probOfDocGivenClass(Instance inst,
                                   int classIndex)

log(N!) + (for all the words)(log(Pi^ni) - log(ni!)) where N is the total number of words Pi is the probability of obtaining word i ni is the number of times the word at index i occurs in the document

Parameters:

inst - The instance to be classified

classIndex - The index of the class we are calculating the probability with respect to

Returns:

The log of the probability of the document occuring given the class

lnFactorial

public double lnFactorial(int n)

Fast computation of ln(n!) for non-negative ints negative ints are passed on to the general gamma-function based version in weka.core.SpecialFunctions if the current n value is higher than any previous one, the cache is extended and filled to cover it the common case is reduced to a simple array lookup

Parameters:

n - the integer

Returns:

ln(n!)

toString

public java.lang.String toString()

main

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

Main method for testing this class.

Parameters:

argv - the options