Package weka.classifiers.rules

Class DecisionTable

  • All Implemented Interfaces:
    java.io.Serializable, java.lang.Cloneable, AdditionalMeasureProducer, CapabilitiesHandler, OptionHandler, RevisionHandler, TechnicalInformationHandler, WeightedInstancesHandler
    Direct Known Subclasses:
    DTNB
    public class DecisionTable
extends Classifier
implements OptionHandler, WeightedInstancesHandler, AdditionalMeasureProducer, TechnicalInformationHandler
    Class for building and using a simple decision table majority classifier.

    For more information see:

    Ron Kohavi: The Power of Decision Tables. In: 8th European Conference on Machine Learning, 174-189, 1995.

    BibTeX: 

     @inproceedings{Kohavi1995,
    author = {Ron Kohavi},
    booktitle = {8th European Conference on Machine Learning},
    pages = {174-189},
    publisher = {Springer},
    title = {The Power of Decision Tables},
    year = {1995}
 }

    Valid options are: 

     -S <search method specification>
  Full class name of search method, followed
  by its options.
  eg: "weka.attributeSelection.BestFirst -D 1"
  (default weka.attributeSelection.BestFirst)
     -X <number of folds>
  Use cross validation to evaluate features.
  Use number of folds = 1 for leave one out CV.
  (Default = leave one out CV)
     -E <acc | rmse | mae | auc>
  Performance evaluation measure to use for selecting attributes.
  (Default = accuracy for discrete class and rmse for numeric class)
     -I
  Use nearest neighbour instead of global table majority.
     -R
  Display decision table rules.
 
     
 Options specific to search method weka.attributeSelection.BestFirst:
 
     -P <start set>
  Specify a starting set of attributes.
  Eg. 1,3,5-7.
     -D <0 = backward | 1 = forward | 2 = bi-directional>
  Direction of search. (default = 1).
     -N <num>
  Number of non-improving nodes to
  consider before terminating search.
     -S <num>
  Size of lookup cache for evaluated subsets.
  Expressed as a multiple of the number of
  attributes in the data set. (default = 1)
    Version:
    $Revision: 12089 $
    Author:
    Mark Hall (mhall@cs.waikato.ac.nz)
    See Also:
    Serialized Form

    • Constructor Detail

      • DecisionTable

        public DecisionTable()
        Constructor for a DecisionTable

    • Method Detail

      • globalInfo

        public java.lang.String globalInfo()
        Returns a string describing classifier
        Returns:
        a description 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
        Returns:
        the technical information about this class

      • listOptions

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

      • crossValTipText

        public java.lang.String crossValTipText()
        Returns the tip text for this property
        Returns:
        tip text for this property suitable for displaying in the explorer/experimenter gui

      • setCrossVal

        public void setCrossVal​(int folds)
        Sets the number of folds for cross validation (1 = leave one out)
        Parameters:
        folds - the number of folds

      • getCrossVal

        public int getCrossVal()
        Gets the number of folds for cross validation
        Returns:
        the number of cross validation folds

      • useIBkTipText

        public java.lang.String useIBkTipText()
        Returns the tip text for this property
        Returns:
        tip text for this property suitable for displaying in the explorer/experimenter gui

      • setUseIBk

        public void setUseIBk​(boolean ibk)
        Sets whether IBk should be used instead of the majority class
        Parameters:
        ibk - true if IBk is to be used

      • getUseIBk

        public boolean getUseIBk()
        Gets whether IBk is being used instead of the majority class
        Returns:
        true if IBk is being used

      • displayRulesTipText

        public java.lang.String displayRulesTipText()
        Returns the tip text for this property
        Returns:
        tip text for this property suitable for displaying in the explorer/experimenter gui

      • setDisplayRules

        public void setDisplayRules​(boolean rules)
        Sets whether rules are to be printed
        Parameters:
        rules - true if rules are to be printed

      • getDisplayRules

        public boolean getDisplayRules()
        Gets whether rules are being printed
        Returns:
        true if rules are being printed

      • searchTipText

        public java.lang.String searchTipText()
        Returns the tip text for this property
        Returns:
        tip text for this property suitable for displaying in the explorer/experimenter gui

      • setSearch

        public void setSearch​(ASSearch search)
        Sets the search method to use
        Parameters:
        search -

      • getSearch

        public ASSearch getSearch()
        Gets the current search method
        Returns:
        the search method used

      • evaluationMeasureTipText

        public java.lang.String evaluationMeasureTipText()
        Returns the tip text for this property
        Returns:
        tip text for this property suitable for displaying in the explorer/experimenter gui

      • getEvaluationMeasure

        public SelectedTag getEvaluationMeasure()
        Gets the currently set performance evaluation measure used for selecting attributes for the decision table
        Returns:
        the performance evaluation measure

      • setEvaluationMeasure

        public void setEvaluationMeasure​(SelectedTag newMethod)
        Sets the performance evaluation measure to use for selecting attributes for the decision table
        Parameters:
        newMethod - the new performance evaluation metric to use

      • setOptions

        public void setOptions​(java.lang.String[] options)
                throws java.lang.Exception
        Parses the options for this object.

        Valid options are: 

         -S <search method specification>
  Full class name of search method, followed
  by its options.
  eg: "weka.attributeSelection.BestFirst -D 1"
  (default weka.attributeSelection.BestFirst)
         -X <number of folds>
  Use cross validation to evaluate features.
  Use number of folds = 1 for leave one out CV.
  (Default = leave one out CV)
         -E <acc | rmse | mae | auc>
  Performance evaluation measure to use for selecting attributes.
  (Default = accuracy for discrete class and rmse for numeric class)
         -I
  Use nearest neighbour instead of global table majority.
         -R
  Display decision table rules.
 
         
 Options specific to search method weka.attributeSelection.BestFirst:
 
         -P <start set>
  Specify a starting set of attributes.
  Eg. 1,3,5-7.
         -D <0 = backward | 1 = forward | 2 = bi-directional>
  Direction of search. (default = 1).
         -N <num>
  Number of non-improving nodes to
  consider before terminating search.
         -S <num>
  Size of lookup cache for evaluated subsets.
  Expressed as a multiple of the number of
  attributes in the data set. (default = 1)
        Specified by:
        setOptions in interface OptionHandler
        Overrides:
        setOptions in class Classifier
        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 classifier.
        Specified by:
        getOptions in interface OptionHandler
        Overrides:
        getOptions in class Classifier
        Returns:
        an array of strings suitable for passing to setOptions

      • buildClassifier

        public void buildClassifier​(Instances data)
                     throws java.lang.Exception
        Generates the classifier.
        Specified by:
        buildClassifier in class Classifier
        Parameters:
        data - set of instances serving as training data
        Throws:
        java.lang.Exception - if the classifier has not been generated successfully

      • distributionForInstance

        public double[] distributionForInstance​(Instance instance)
                                 throws java.lang.Exception
        Calculates the class membership probabilities for the given test instance.
        Overrides:
        distributionForInstance in class Classifier
        Parameters:
        instance - the instance to be classified
        Returns:
        predicted class probability distribution
        Throws:
        java.lang.Exception - if distribution can't be computed

      • printFeatures

        public java.lang.String printFeatures()
        Returns a string description of the features selected
        Returns:
        a string of features

      • measureNumRules

        public double measureNumRules()
        Returns the number of rules
        Returns:
        the number of rules

      • enumerateMeasures

        public java.util.Enumeration enumerateMeasures()
        Returns an enumeration of the additional measure names
        Specified by:
        enumerateMeasures in interface AdditionalMeasureProducer
        Returns:
        an enumeration of the measure names

      • getMeasure

        public double getMeasure​(java.lang.String additionalMeasureName)
        Returns the value of the named measure
        Specified by:
        getMeasure in interface AdditionalMeasureProducer
        Parameters:
        additionalMeasureName - the name of the measure to query for its value
        Returns:
        the value of the named measure
        Throws:
        java.lang.IllegalArgumentException - if the named measure is not supported

      • toString

        public java.lang.String toString()
        Returns a description of the classifier.
        Overrides:
        toString in class java.lang.Object
        Returns:
        a description of the classifier as a string.

      • main

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