Class FilteredAssociator

  • All Implemented Interfaces:
    java.io.Serializable, java.lang.Cloneable, Associator, CapabilitiesHandler, OptionHandler, RevisionHandler

    public class FilteredAssociator
    extends SingleAssociatorEnhancer
    Class for running an arbitrary associator on data that has been passed through an arbitrary filter. Like the associator, the structure of the filter is based exclusively on the training data and test instances will be processed by the filter without changing their structure.

    Valid options are:

     -F <filter specification>
      Full class name of filter to use, followed
      by filter options.
      eg: "weka.filters.unsupervised.attribute.Remove -V -R 1,2"
      (default: weka.filters.MultiFilter with
      weka.filters.unsupervised.attribute.ReplaceMissingValues)
     -c <the class index>
      The class index.
      (default: -1, i.e. unset)
     -W
      Full name of base associator.
      (default: weka.associations.Apriori)
     
     Options specific to associator weka.associations.Apriori:
     
     -N <required number of rules output>
      The required number of rules. (default = 10)
     -T <0=confidence | 1=lift | 2=leverage | 3=Conviction>
      The metric type by which to rank rules. (default = confidence)
     -C <minimum metric score of a rule>
      The minimum confidence of a rule. (default = 0.9)
     -D <delta for minimum support>
      The delta by which the minimum support is decreased in
      each iteration. (default = 0.05)
     -U <upper bound for minimum support>
      Upper bound for minimum support. (default = 1.0)
     -M <lower bound for minimum support>
      The lower bound for the minimum support. (default = 0.1)
     -S <significance level>
      If used, rules are tested for significance at
      the given level. Slower. (default = no significance testing)
     -I
      If set the itemsets found are also output. (default = no)
     -R
      Remove columns that contain all missing values (default = no)
     -V
      Report progress iteratively. (default = no)
     -A
      If set class association rules are mined. (default = no)
     -c <the class index>
      The class index. (default = last)
    Version:
    $Revision: 5504 $
    Author:
    Len Trigg (trigg@cs.waikato.ac.nz), FracPete (fracpete at waikato dot ac dot nz)
    See Also:
    Serialized Form
    • Constructor Detail

      • FilteredAssociator

        public FilteredAssociator()
        Default constructor.
    • Method Detail

      • globalInfo

        public java.lang.String globalInfo()
        Returns a string describing this Associator
        Returns:
        a description of the Associator suitable for displaying in the explorer/experimenter gui
      • setOptions

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

        Valid options are:

         -F <filter specification>
          Full class name of filter to use, followed
          by filter options.
          eg: "weka.filters.unsupervised.attribute.Remove -V -R 1,2"
          (default: weka.filters.MultiFilter with
          weka.filters.unsupervised.attribute.ReplaceMissingValues)
         -c <the class index>
          The class index.
          (default: -1, i.e. unset)
         -W
          Full name of base associator.
          (default: weka.associations.Apriori)
         
         Options specific to associator weka.associations.Apriori:
         
         -N <required number of rules output>
          The required number of rules. (default = 10)
         -T <0=confidence | 1=lift | 2=leverage | 3=Conviction>
          The metric type by which to rank rules. (default = confidence)
         -C <minimum metric score of a rule>
          The minimum confidence of a rule. (default = 0.9)
         -D <delta for minimum support>
          The delta by which the minimum support is decreased in
          each iteration. (default = 0.05)
         -U <upper bound for minimum support>
          Upper bound for minimum support. (default = 1.0)
         -M <lower bound for minimum support>
          The lower bound for the minimum support. (default = 0.1)
         -S <significance level>
          If used, rules are tested for significance at
          the given level. Slower. (default = no significance testing)
         -I
          If set the itemsets found are also output. (default = no)
         -R
          Remove columns that contain all missing values (default = no)
         -V
          Report progress iteratively. (default = no)
         -A
          If set class association rules are mined. (default = no)
         -c <the class index>
          The class index. (default = last)
        Specified by:
        setOptions in interface OptionHandler
        Overrides:
        setOptions in class SingleAssociatorEnhancer
        Parameters:
        options - the list of options as an array of strings
        Throws:
        java.lang.Exception - if an option is not supported
      • filterTipText

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

        public void setFilter​(Filter value)
        Sets the filter
        Parameters:
        value - the filter with all options set.
      • getFilter

        public Filter getFilter()
        Gets the filter used.
        Returns:
        the current filter
      • classIndexTipText

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

        public void setClassIndex​(int value)
        Sets the class index
        Parameters:
        value - the class index
      • getClassIndex

        public int getClassIndex()
        Gets the class index
        Returns:
        the index of the class attribute
      • buildAssociations

        public void buildAssociations​(Instances data)
                               throws java.lang.Exception
        Build the associator on the filtered data.
        Parameters:
        data - the training data
        Throws:
        java.lang.Exception - if the Associator could not be built successfully
      • toString

        public java.lang.String toString()
        Output a representation of this associator
        Overrides:
        toString in class java.lang.Object
        Returns:
        a representation of this associator
      • main

        public static void main​(java.lang.String[] args)
        Main method for running this class.
        Parameters:
        args - commandline arguments, use "-h" for full list