/* * 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); } }