Package weka.classifiers.bayes.net.search.local

Class TabuSearch

  • All Implemented Interfaces:
    java.io.Serializable, OptionHandler, RevisionHandler, TechnicalInformationHandler
    public class TabuSearch
extends HillClimber
implements TechnicalInformationHandler
    This Bayes Network learning algorithm uses tabu search for finding a well scoring Bayes network structure. Tabu search is hill climbing till an optimum is reached. The following step is the least worst possible step. The last X steps are kept in a list and none of the steps in this so called tabu list is considered in taking the next step. The best network found in this traversal is returned.

    For more information see:

    R.R. Bouckaert (1995). Bayesian Belief Networks: from Construction to Inference. Utrecht, Netherlands.

    BibTeX: 

     @phdthesis{Bouckaert1995,
    address = {Utrecht, Netherlands},
    author = {R.R. Bouckaert},
    institution = {University of Utrecht},
    title = {Bayesian Belief Networks: from Construction to Inference},
    year = {1995}
 }

    Valid options are: 

     -L <integer>
  Tabu list length
     -U <integer>
  Number of runs
     -P <nr of parents>
  Maximum number of parents
     -R
  Use arc reversal operation.
  (default false)
     -P <nr of parents>
  Maximum number of parents
     -R
  Use arc reversal operation.
  (default false)
     -N
  Initial structure is empty (instead of Naive Bayes)
     -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 [BAYES|MDL|ENTROPY|AIC|CROSS_CLASSIC|CROSS_BAYES]
  Score type (BAYES, BDeu, MDL, ENTROPY and AIC)
    Version:
    $Revision: 1.5 $
    Author:
    Remco Bouckaert (rrb@xm.co.nz)
    See Also:
    Serialized Form

    • Constructor Detail

      • TabuSearch

        public TabuSearch()

    • 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

      • getRuns

        public int getRuns()
        Returns:
        number of runs

      • setRuns

        public void setRuns​(int nRuns)
        Sets the number of runs
        Parameters:
        nRuns - The number of runs to set

      • getTabuList

        public int getTabuList()
        Returns:
        the Tabu List length

      • setTabuList

        public void setTabuList​(int nTabuList)
        Sets the Tabu List length.
        Parameters:
        nTabuList - The nTabuList to set

      • listOptions

        public java.util.Enumeration listOptions()
        Returns an enumeration describing the available options.
        Specified by:
        listOptions in interface OptionHandler
        Overrides:
        listOptions in class HillClimber
        Returns:
        an enumeration of all the available options.

      • setOptions

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

        Valid options are: 

         -L <integer>
  Tabu list length
         -U <integer>
  Number of runs
         -P <nr of parents>
  Maximum number of parents
         -R
  Use arc reversal operation.
  (default false)
         -P <nr of parents>
  Maximum number of parents
         -R
  Use arc reversal operation.
  (default false)
         -N
  Initial structure is empty (instead of Naive Bayes)
         -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 [BAYES|MDL|ENTROPY|AIC|CROSS_CLASSIC|CROSS_BAYES]
  Score type (BAYES, BDeu, MDL, ENTROPY and AIC)
        Specified by:
        setOptions in interface OptionHandler
        Overrides:
        setOptions in class HillClimber
        Parameters:
        options - the list of options as an array of strings
        Throws:
        java.lang.Exception - if an option is not supported

      • getOptions

        public java.lang.String[] getOptions()
        Gets the current settings of the search algorithm.
        Specified by:
        getOptions in interface OptionHandler
        Overrides:
        getOptions in class HillClimber
        Returns:
        an array of strings suitable for passing to setOptions

      • globalInfo

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

      • runsTipText

        public java.lang.String runsTipText()
        Returns:
        a string to describe the Runs option.

      • tabuListTipText

        public java.lang.String tabuListTipText()
        Returns:
        a string to describe the TabuList option.