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Class weka.classifiers.bayes.NaiveBayesUpdateable 

java.lang.Object
    |
    +----weka.classifiers.Classifier
            |
            +----weka.classifiers.DistributionClassifier
                    |
                    +----weka.classifiers.bayes.NaiveBayes
                            |
                            +----weka.classifiers.bayes.NaiveBayesUpdateable
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: 1.3 $
Author:
Len Trigg (trigg@cs.waikato.ac.nz)
Author:
Eibe Frank (eibe@cs.waikato.ac.nz)

Constructor Index

o NaiveBayesUpdateable()
 

Method Index

o main(String[])
Main method for testing this class.
o setUseSupervisedDiscretization(boolean)
Set whether supervised discretization is to be used.

Constructor Detail

o NaiveBayesUpdateable
public NaiveBayesUpdateable()

Method Detail

o setUseSupervisedDiscretization
public void setUseSupervisedDiscretization(boolean newblah)
          Set whether supervised discretization is to be used.
Parameters:
newblah - true if supervised discretization is to be used.
Overrides:
setUseSupervisedDiscretization in class NaiveBayes
o main
public static void main(java.lang.String argv[])
          Main method for testing this class.
Parameters:
argv - the options 
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