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## weka.classifiers.bayes
Class NaiveBayesSimple

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

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

    public class NaiveBayesSimple

extends Classifier

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: 1.13.2.2 $
Author:
  Eibe Frank (eibe@cs.waikato.ac.nz)
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.
`java.lang.String` | `globalInfo()` Returns a string describing this classifier
`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.Classifier
`classifyInstance, debugTipText, forName, getDebug, getOptions, listOptions, makeCopies, makeCopy, setDebug, setOptions`

Methods inherited from class java.lang.Object
`equals, getClass, hashCode, notify, notifyAll, wait, wait, wait`

Constructor Detail

### NaiveBayesSimple

    public NaiveBayesSimple()

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 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

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