weka.classifiers.bayes
Class NaiveBayesUpdateable

java.lang.Object
  |
  +--weka.classifiers.Classifier
        |
        +--weka.classifiers.bayes.NaiveBayes
              |
              +--weka.classifiers.bayes.NaiveBayesUpdateable
All Implemented Interfaces:
java.lang.Cloneable, OptionHandler, java.io.Serializable, UpdateableClassifier, WeightedInstancesHandler

public class NaiveBayesUpdateable
extends NaiveBayes
implements UpdateableClassifier

Class for a Naive Bayes classifier using estimator classes. This is the updateable version of NaiveBayes. This classifier will use a default precision of 0.1 for numeric attributes when buildClassifier is called with zero training instances.

For more information on Naive Bayes classifiers, see

George H. John and Pat Langley (1995). Estimating Continuous Distributions in Bayesian Classifiers. Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence. pp. 338-345. Morgan Kaufmann, San Mateo.

Valid options are:

-K
Use kernel estimation for modelling numeric attributes rather than a single normal distribution.

Version:
$Revision: 1.4 $
Author:
Len Trigg (trigg@cs.waikato.ac.nz), Eibe Frank (eibe@cs.waikato.ac.nz)
See Also:
Serialized Form

Constructor Summary
NaiveBayesUpdateable()
           
 
Method Summary
 java.lang.String globalInfo()
          Returns a string describing this classifier
static void main(java.lang.String[] argv)
          Main method for testing this class.
 void setUseSupervisedDiscretization(boolean newblah)
          Set whether supervised discretization is to be used.
 
Methods inherited from class weka.classifiers.bayes.NaiveBayes
buildClassifier, distributionForInstance, getOptions, getUseKernelEstimator, getUseSupervisedDiscretization, listOptions, setOptions, setUseKernelEstimator, toString, updateClassifier, useKernelEstimatorTipText, useSupervisedDiscretizationTipText
 
Methods inherited from class weka.classifiers.Classifier
classifyInstance, debugTipText, forName, getDebug, makeCopies, setDebug
 
Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait
 
Methods inherited from interface weka.classifiers.UpdateableClassifier
updateClassifier
 

Constructor Detail

NaiveBayesUpdateable

public NaiveBayesUpdateable()
Method Detail

globalInfo

public java.lang.String globalInfo()
Returns a string describing this classifier

Overrides:
globalInfo in class NaiveBayes
Returns:
a description of the classifier suitable for displaying in the explorer/experimenter gui

setUseSupervisedDiscretization

public void setUseSupervisedDiscretization(boolean newblah)
Set whether supervised discretization is to be used.

Overrides:
setUseSupervisedDiscretization in class NaiveBayes
Parameters:
newblah - true if supervised discretization is to be used.

main

public static void main(java.lang.String[] argv)
Main method for testing this class.

Parameters:
argv - the options


Copyright (c) 2003 David Lindsay, Computer Learning Research Centre, Dept. Computer Science, Royal Holloway, University of London