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.