Package weka.classifiers.bayes

Class NaiveBayesSimple

  • All Implemented Interfaces:
    java.io.Serializable, java.lang.Cloneable, CapabilitiesHandler, OptionHandler, RevisionHandler, TechnicalInformationHandler
    public class NaiveBayesSimple
extends Classifier
implements TechnicalInformationHandler
    Class for building and using a simple Naive Bayes classifier.Numeric attributes are modelled by a normal distribution.

    For more information, see

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

    BibTeX: 

     @book{Duda1973,
    address = {New York},
    author = {Richard Duda and Peter Hart},
    publisher = {Wiley},
    title = {Pattern Classification and Scene Analysis},
    year = {1973}
 }

    Valid options are: 

     -D
  If set, classifier is run in debug mode and
  may output additional info to the console
    Version:
    $Revision: 5516 $
    Author:
    Eibe Frank (eibe@cs.waikato.ac.nz)
    See Also:
    Serialized Form

    • 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

      • getTechnicalInformation

        public TechnicalInformation getTechnicalInformation()
        Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
        Specified by:
        getTechnicalInformation in interface TechnicalInformationHandler
        Returns:
        the technical information about this class

      • 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