Package weka.classifiers.bayes

Class NaiveBayesUpdateable

java.lang.Object
weka.classifiers.AbstractClassifier
weka.classifiers.bayes.NaiveBayes
weka.classifiers.bayes.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.

BibTeX: 

 @inproceedings{John1995,
    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: 

 -K
  Use kernel density estimator rather than normal
  distribution for numeric attributes
 -D
  Use supervised discretization to process numeric attributes
 
 -O
  Display model in old format (good when there are many classes)
Version:
$Revision: 8034 $
Author:
Len Trigg (trigg@cs.waikato.ac.nz), Eibe Frank (eibe@cs.waikato.ac.nz)
See Also:

  • Constructor Details

    • NaiveBayesUpdateable

      public NaiveBayesUpdateable()

  • Method Details

    • globalInfo

      public 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

    • 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
      Overrides:
      getTechnicalInformation in class NaiveBayes
      Returns:
      the technical information about this class

    • 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.

    • getRevision

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

    • main

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