LFSMethods (original) (raw)

• java.lang.Object

• • weka.attributeSelection.LFSMethods

• All Implemented Interfaces:
  RevisionHandler

public class LFSMethods
extends java.lang.Object
implements RevisionHandler
Version: Revision:1.3Revision: 1.3 Revision:1.3
Author:
Martin Guetlein (martin.guetlein@gmail.com)

• • Nested Class Summary

  Nested Classes

  Modifier and Type	Class and Description
  class	LFSMethods.Link2 Class for a node in a linked list.
  class	LFSMethods.LinkedList2 Class for handling a linked list.

  • Constructor Summary

  Constructors

  Constructor and Description
  LFSMethods() empty constructor methods are not static because of access to inner class Link2 and LinkedList2

  • Method Summary

  All Methods Instance Methods Concrete Methods

  Modifier and Type	Method and Description
  java.util.BitSet	floatingForwardSearch(int cacheSize, java.util.BitSet startGroup, int[] ranking, int k, boolean incrementK, int maxStale,Instances data,SubsetEvaluator evaluator, boolean verbose) Performs linear floating forward selection ( the stopping criteria cannot be changed to a specific size value )
  java.util.BitSet	forwardSearch(int cacheSize, java.util.BitSet startGroup, int[] ranking, int k, boolean incrementK, int maxStale, int forceResultSize,Instances data,SubsetEvaluator evaluator, boolean verbose) Performs linear forward selection
  java.util.BitSet	getBestGroup()
  java.util.BitSet	getBestGroupOfSize(int size)
  double	getBestMerit()
  int	getNumEvalsCached()
  int	getNumEvalsTotal()
  java.lang.String	getRevision() Returns the revision string.
  int[]	rankAttributes(Instances data,SubsetEvaluator evaluator, boolean verbose)

     * ### Methods inherited from class java.lang.Object  
     `equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

• • Constructor Detail

     * #### LFSMethods  
     public LFSMethods()  
     empty constructor methods are not static because of access to inner class Link2 and LinkedList2  

  • Method Detail

    * #### getBestGroup  
    public java.util.BitSet getBestGroup()  
    Returns:  
    best group found by forwardSearch/floatingForwardSearch  
    * #### getBestMerit  
    public double getBestMerit()  
    Returns:  
    merit of best group found by forwardSearch/floatingForwardSearch  
    * #### getBestGroupOfSize  
    public java.util.BitSet getBestGroupOfSize(int size)  
    Returns:  
    best group of size found by forwardSearch  
    * #### getNumEvalsCached  
    public int getNumEvalsCached()  
    Returns:  
    number of cached / not performed evaluations  
    * #### getNumEvalsTotal  
    public int getNumEvalsTotal()  
    Returns:  
    number totally performed evaluations  
    * #### rankAttributes  
    public int[] rankAttributes([Instances](../../weka/core/Instances.html "class in weka.core") data,  
                                [SubsetEvaluator](../../weka/attributeSelection/SubsetEvaluator.html "interface in weka.attributeSelection") evaluator,  
                                boolean verbose)  
                         throws java.lang.Exception  
    Returns:  
    ranking (integer array) of attributes in data with evaluator (sorting is NOT stable!)  
    Throws:  
    `java.lang.Exception`  
    * #### forwardSearch  
    public java.util.BitSet forwardSearch(int cacheSize,  
                                          java.util.BitSet startGroup,  
                                          int[] ranking,  
                                          int k,  
                                          boolean incrementK,  
                                          int maxStale,  
                                          int forceResultSize,  
                                          [Instances](../../weka/core/Instances.html "class in weka.core") data,  
                                          [SubsetEvaluator](../../weka/attributeSelection/SubsetEvaluator.html "interface in weka.attributeSelection") evaluator,  
                                          boolean verbose)  
                                   throws java.lang.Exception  
    Performs linear forward selection  
    Parameters:  
    `cacheSize` \- chacheSize (times number of instances) to store already evaluated sets  
    `startGroup` \- start group for search (can be null)  
    `ranking` \- ranking of attributes (as produced by rankAttributes), no ranking would be \[0,1,2,3,4..\]  
    `k` \- number of top k attributes that are taken into account  
    `incrementK` \- true -> fixed-set, false -> fixed-width  
    `maxStale` \- number of times the search proceeds even though no improvement was found (1 = hill-climbing)  
    `forceResultSize` \- stopping criteria changed from no-improvement (forceResultSize=-1) to subset-size  
    `data` \-  
    `evaluator` \-  
    `verbose` \-  
    Returns:  
    BitSet, that cotains the best-group found  
    Throws:  
    `java.lang.Exception`  
    * #### floatingForwardSearch  
    public java.util.BitSet floatingForwardSearch(int cacheSize,  
                                                  java.util.BitSet startGroup,  
                                                  int[] ranking,  
                                                  int k,  
                                                  boolean incrementK,  
                                                  int maxStale,  
                                                  [Instances](../../weka/core/Instances.html "class in weka.core") data,  
                                                  [SubsetEvaluator](../../weka/attributeSelection/SubsetEvaluator.html "interface in weka.attributeSelection") evaluator,  
                                                  boolean verbose)  
                                           throws java.lang.Exception  
    Performs linear floating forward selection ( the stopping criteria cannot be changed to a specific size value )  
    Parameters:  
    `cacheSize` \- chacheSize (times number of instances) to store already evaluated sets  
    `startGroup` \- start group for search (can be null)  
    `ranking` \- ranking of attributes (as produced by rankAttributes), no ranking would be \[0,1,2,3,4..\]  
    `k` \- number of top k attributes that are taken into account  
    `incrementK` \- true -> fixed-set, false -> fixed-width  
    `maxStale` \- number of times the search proceeds even though no improvement was found (1 = hill-climbing)  
    `data` \-  
    `evaluator` \-  
    `verbose` \-  
    Returns:  
    BitSet, that cotains the best-group found  
    Throws:  
    `java.lang.Exception`  
    * #### getRevision  
    public java.lang.String getRevision()  
    Returns the revision string.  
    Specified by:  
    `[getRevision](../../weka/core/RevisionHandler.html#getRevision--)` in interface `[RevisionHandler](../../weka/core/RevisionHandler.html "interface in weka.core")`  
    Returns:  
    the revision