/* * This program is free software; you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation; either version 2 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program; if not, write to the Free Software * Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA. */ /* * CostSensitiveAttributeEval.java * Copyright (C) 2008 University of Waikato, Hamilton, New Zealand * */ package weka.attributeSelection; import weka.core.OptionHandler; import weka.core.RevisionUtils; import java.util.BitSet; import java.io.Serializable; /** * A meta subset evaluator that makes its base subset evaluator cost-sensitive. *

* * Valid options are:

* *

 -C <cost file name>
 *  File name of a cost matrix to use. If this is not supplied,
 *  a cost matrix will be loaded on demand. The name of the
 *  on-demand file is the relation name of the training data
 *  plus ".cost", and the path to the on-demand file is
 *  specified with the -N option.
* *
 -N <directory>
 *  Name of a directory to search for cost files when loading
 *  costs on demand (default current directory).
* *
 -cost-matrix <matrix>
 *  The cost matrix in Matlab single line format.
* *
 -S <integer>
 *  The seed to use for random number generation.
* *
 -W
 *  Full name of base evaluator.
 *  (default: weka.attributeSelection.ReliefFAttributeEval)
* *
 
 * Options specific to evaluator weka.attributeSelection.ReliefFAttributeEval:
 * 
* *
 -M <num instances>
 *  Specify the number of instances to
 *  sample when estimating attributes.
 *  If not specified, then all instances
 *  will be used.
* *
 -D <seed>
 *  Seed for randomly sampling instances.
 *  (Default = 1)
* *
 -K <number of neighbours>
 *  Number of nearest neighbours (k) used
 *  to estimate attribute relevances
 *  (Default = 10).
* *
 -W
 *  Weight nearest neighbours by distance
* *
 -A <num>
 *  Specify sigma value (used in an exp
 *  function to control how quickly
 *  weights for more distant instances
 *  decrease. Use in conjunction with -W.
 *  Sensible value=1/5 to 1/10 of the
 *  number of nearest neighbours.
 *  (Default = 2)
* * * @author Mark Hall (mhall{[at]}pentaho{[dot]}com) * @version $Revision: 5563 $ */ public class CostSensitiveAttributeEval extends CostSensitiveASEvaluation implements Serializable, AttributeEvaluator, OptionHandler { /** For serialization */ static final long serialVersionUID = 4484876541145458447L; /** * Default constructor. */ public CostSensitiveAttributeEval() { setEvaluator(new ReliefFAttributeEval()); } /** * Return the name of the default evaluator. * * @return the name of the default evaluator */ public String defaultEvaluatorString() { return "weka.attributeSelection.ReliefFAttributeEval"; } /** * Set the base evaluator. * * @param newEvaluator the evaluator to use. * @throws IllegalArgumentException if the evaluator is not an instance of AttributeEvaluator */ public void setEvaluator(ASEvaluation newEvaluator) throws IllegalArgumentException { if (!(newEvaluator instanceof AttributeEvaluator)) { throw new IllegalArgumentException("Evaluator must be an AttributeEvaluator!"); } m_evaluator = newEvaluator; } /** * Evaluates an individual attribute. Delegates the actual evaluation to the * base attribute evaluator. * * @param attribute the index of the attribute to be evaluated * @return the "merit" of the attribute * @exception Exception if the attribute could not be evaluated */ public double evaluateAttribute(int attribute) throws Exception { return ((AttributeEvaluator)m_evaluator).evaluateAttribute(attribute); } /** * Returns the revision string. * * @return the revision */ public String getRevision() { return RevisionUtils.extract("$Revision: 5563 $"); } /** * Main method for testing this class. * * @param args the options */ public static void main (String[] args) { runEvaluator(new CostSensitiveAttributeEval(), args); } }