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## weka.classifiers.bayes
Class NaiveBayesUpdateable

    java.lang.Object
      weka.classifiers.Classifier
          weka.classifiers.bayes.NaiveBayes
              weka.classifiers.bayes.NaiveBayesUpdateable

All Implemented Interfaces:
  java.io.Serializable, java.lang.Cloneable, UpdateableClassifier, OptionHandler, 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, makeCopy, 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

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