All Implemented Interfaces:
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: 10154 $
Author:
Remco Bouckaert
See Also:
  • Constructor Details

    • TAN

      public TAN()
  • Method Details

    • 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 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:
      Exception - if something goes wrong
    • listOptions

      public Enumeration<Option> listOptions()
      Returns an enumeration describing the available options.
      Specified by:
      listOptions in interface OptionHandler
      Overrides:
      listOptions in class GlobalScoreSearchAlgorithm
      Returns:
      an enumeration of all the available options.
    • setOptions

      public void setOptions(String[] options) throws 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:
      Exception - if an option is not supported
    • getOptions

      public String[] getOptions()
      Gets the current settings of the Classifier.
      Specified by:
      getOptions in interface OptionHandler
      Overrides:
      getOptions in class GlobalScoreSearchAlgorithm
      Returns:
      an array of strings suitable for passing to setOptions
    • globalInfo

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

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