Package weka.classifiers.bayes.net.search.global

Class TAN

  • All Implemented Interfaces:
    java.io.Serializable, OptionHandler, RevisionHandler, TechnicalInformationHandler
    public class TAN
extends GlobalScoreSearchAlgorithm
implements TechnicalInformationHandler
    This Bayes Network learning algorithm determines the maximum weight spanning tree and returns a Naive Bayes network augmented with a tree.

    For more information see:

    N. Friedman, D. Geiger, M. Goldszmidt (1997). Bayesian network classifiers. Machine Learning. 29(2-3):131-163.

    BibTeX: 

     @article{Friedman1997,
    author = {N. Friedman and D. Geiger and M. Goldszmidt},
    journal = {Machine Learning},
    number = {2-3},
    pages = {131-163},
    title = {Bayesian network classifiers},
    volume = {29},
    year = {1997}
 }

    Valid options are: 

     -mbc
  Applies a Markov Blanket correction to the network structure, 
  after a network structure is learned. This ensures that all 
  nodes in the network are part of the Markov blanket of the 
  classifier node.
     -S [LOO-CV|k-Fold-CV|Cumulative-CV]
  Score type (LOO-CV,k-Fold-CV,Cumulative-CV)
     -Q
  Use probabilistic or 0/1 scoring.
  (default probabilistic scoring)
    Version:
    $Revision: 1.7 $
    Author:
    Remco Bouckaert
    See Also:
    Serialized Form

    • Constructor Detail

      • TAN

        public TAN()

    • Method Detail

      • 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

      • buildStructure

        public void buildStructure​(BayesNet bayesNet,
                           Instances instances)
                    throws java.lang.Exception
        buildStructure determines the network structure/graph of the network using the maximimum weight spanning tree algorithm of Chow and Liu
        Overrides:
        buildStructure in class SearchAlgorithm
        Parameters:
        bayesNet -
        instances -
        Throws:
        java.lang.Exception - if something goes wrong

      • setOptions

        public void setOptions​(java.lang.String[] options)
                throws java.lang.Exception
        Parses a given list of options.

        Valid options are: 

         -mbc
  Applies a Markov Blanket correction to the network structure, 
  after a network structure is learned. This ensures that all 
  nodes in the network are part of the Markov blanket of the 
  classifier node.
         -S [LOO-CV|k-Fold-CV|Cumulative-CV]
  Score type (LOO-CV,k-Fold-CV,Cumulative-CV)
         -Q
  Use probabilistic or 0/1 scoring.
  (default probabilistic scoring)
        Specified by:
        setOptions in interface OptionHandler
        Overrides:
        setOptions in class GlobalScoreSearchAlgorithm
        Parameters:
        options - the list of options as an array of strings
        Throws:
        java.lang.Exception - if an option is not supported

      • globalInfo

        public java.lang.String globalInfo()
        This will return a string describing the classifier.
        Overrides:
        globalInfo in class GlobalScoreSearchAlgorithm
        Returns:
        The string.