weka.classifiers
Class NaiveBayesSimple

java.lang.Object
  weka.classifiers.Classifier
      weka.classifiers.DistributionClassifier
          weka.classifiers.NaiveBayesSimple

All Implemented Interfaces:

java.io.Serializable, java.lang.Cloneable

public class NaiveBayesSimple
extends DistributionClassifier

Class for building and using a simple Naive Bayes classifier. Numeric attributes are modelled by a normal distribution. For more information, see

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

Version:

$Revision: 1.1 $

Author:

Eibe Frank ([email protected])

See Also:

Serialized Form

Constructor Summary

NaiveBayesSimple()

Method Summary

void	buildClassifier(Instances instances) Generates the classifier.
double[]	distributionForInstance(Instance instance) Calculates the class membership probabilities for the given test instance.
static void	main(java.lang.String[] argv) Main method for testing this class.
java.lang.String	toString() Returns a description of the classifier.

Methods inherited from class weka.classifiers.DistributionClassifier

classifyInstance

Methods inherited from class weka.classifiers.Classifier

forName, makeCopies

Methods inherited from class java.lang.Object

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

Constructor Detail

NaiveBayesSimple

public NaiveBayesSimple()

Method Detail

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.

Specified by:

distributionForInstance in class DistributionClassifier

Parameters:

instance - the instance to be classified

Returns:

predicted class probability distribution

Throws:

java.lang.Exception - if distribution can't be computed

toString

public java.lang.String toString()

Returns a description of the classifier.

Overrides:

toString in class java.lang.Object

Returns:

a description of the classifier as a string.

main

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

Main method for testing this class.

Parameters:

argv - the options