Package weka.attributeSelection

Interface RankedOutputSearch

All Known Implementing Classes:
GreedyStepwise, Ranker
public interface RankedOutputSearch
Interface for search methods capable of producing a ranked list of attributes.
Version:
$Revision: 8034 $
Author:
Mark Hall (mhall@cs.waikato.ac.nz)

  • Method Summary

    Modifier and Type
    Method
    Description
    int
    getCalculatedNumToSelect()
    Gets the calculated number of attributes to retain.
    boolean
    getGenerateRanking()
    Gets whether the user has opted to see a ranked list of attributes rather than the normal result of the search
    int
    getNumToSelect()
    Gets the user specified number of attributes to be retained.
    double
    getThreshold()
    Gets the threshold by which attributes can be discarded.
    double[][]
    rankedAttributes()
    Returns a X by 2 list of attribute indexes and corresponding evaluations from best (highest) to worst.
    void
    setGenerateRanking(boolean doRanking)
    Sets whether or not ranking is to be performed.
    void
    setNumToSelect(int numToSelect)
    Specify the number of attributes to select from the ranked list.
    void
    setThreshold(double threshold)
    Sets a threshold by which attributes can be discarded from the ranking.

  • Method Details

    • rankedAttributes

      double[][] rankedAttributes() throws Exception
      Returns a X by 2 list of attribute indexes and corresponding evaluations from best (highest) to worst.
      Returns:
      the ranked list of attribute indexes in an array of ints
      Throws:
      Exception - if the ranking can't be produced

    • setThreshold

      void setThreshold(double threshold)
      Sets a threshold by which attributes can be discarded from the ranking. This threshold is used by the AttributeSelection module which does the actual discarding of attributes---the implementer of this method needs only to provide a variable in which to store the supplied threshold. -Double.MAX_VALUE is reserved to mean no threshold, ie, retain all attributes.
      Parameters:
      threshold - the threshold.

    • getThreshold

      double getThreshold()
      Gets the threshold by which attributes can be discarded. Discarding of attributes is done by the AttributeSelection module using the threshold returned by this method.
      Returns:
      a threshold by which to discard attributes

    • setNumToSelect

      void setNumToSelect(int numToSelect)
      Specify the number of attributes to select from the ranked list. < 0 indicates that all attributes are to be retained. NumToSelect has precedence over threshold, ie. if there is a non -1 value for NumToSelect then this will take precedence over any threshold value.
      Parameters:
      numToSelect - the number of attributes to retain

    • getNumToSelect

      int getNumToSelect()
      Gets the user specified number of attributes to be retained.
      Returns:
      the number of attributes to retain

    • getCalculatedNumToSelect

      int getCalculatedNumToSelect()
      Gets the calculated number of attributes to retain. This is the actual number of attributes to retain. This is the same as getNumToSelect if the user specifies a number which is not less than zero. Otherwise it should be the number of attributes in the (potentially transformed) data.

    • setGenerateRanking

      void setGenerateRanking(boolean doRanking)
      Sets whether or not ranking is to be performed. When a search method is capable of producing a ranked list of attributes, the user has the choice of seeing the results of a normal search or seeing a ranked list.
      Parameters:
      doRanking - true if ranked list is to be produced

    • getGenerateRanking

      boolean getGenerateRanking()
      Gets whether the user has opted to see a ranked list of attributes rather than the normal result of the search
      Returns:
      true if a ranked list has been requested.