Class NaiveBayesUpdateable

All Implemented Interfaces:
Serializable, Cloneable, Classifier, UpdateableClassifier, Aggregateable<NaiveBayes>, BatchPredictor, CapabilitiesHandler, CapabilitiesIgnorer, CommandlineRunnable, OptionHandler, RevisionHandler, TechnicalInformationHandler, WeightedAttributesHandler, 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, Pat Langley: Estimating Continuous Distributions in Bayesian Classifiers. In: Eleventh Conference on Uncertainty in Artificial Intelligence, San Mateo, 338-345, 1995.


    address = {San Mateo},
    author = {George H. John and Pat Langley},
    booktitle = {Eleventh Conference on Uncertainty in Artificial Intelligence},
    pages = {338-345},
    publisher = {Morgan Kaufmann},
    title = {Estimating Continuous Distributions in Bayesian Classifiers},
    year = {1995}

Valid options are:

  Use kernel density estimator rather than normal
  distribution for numeric attributes
  Use supervised discretization to process numeric attributes
  Display model in old format (good when there are many classes)
$Revision: 8034 $
Len Trigg (, Eibe Frank (
See Also:
  • Constructor Details

    • NaiveBayesUpdateable

      public NaiveBayesUpdateable()
  • Method Details

    • globalInfo

      public String globalInfo()
      Returns a string describing this classifier
      globalInfo in class NaiveBayes
      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
      getTechnicalInformation in class NaiveBayes
      the technical information about this class
    • setUseSupervisedDiscretization

      public void setUseSupervisedDiscretization(boolean newblah)
      Set whether supervised discretization is to be used.
      setUseSupervisedDiscretization in class NaiveBayes
      newblah - true if supervised discretization is to be used.
    • getRevision

      public String getRevision()
      Returns the revision string.
      Specified by:
      getRevision in interface RevisionHandler
      getRevision in class NaiveBayes
      the revision
    • main

      public static void main(String[] argv)
      Main method for testing this class.
      argv - the options