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The Waikato Environment for Knowledge Analysis (WEKA), a machine learning workbench. This is the stable version. Apart from bugfixes, this version does not receive any other updates.

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/*
 *   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 3 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, see .
 */

/*
 *    CostSensitiveClassifierSplitEvaluator.java
 *    Copyright (C) 2002-2012 University of Waikato, Hamilton, New Zealand
 *
 */

package weka.experiment;

import java.io.BufferedReader;
import java.io.ByteArrayOutputStream;
import java.io.File;
import java.io.FileReader;
import java.io.ObjectOutputStream;
import java.lang.management.ManagementFactory;
import java.lang.management.ThreadMXBean;
import java.util.Collections;
import java.util.Enumeration;
import java.util.Vector;

import weka.classifiers.AbstractClassifier;
import weka.classifiers.CostMatrix;
import weka.classifiers.Evaluation;
import weka.core.AdditionalMeasureProducer;
import weka.core.Attribute;
import weka.core.Instances;
import weka.core.Option;
import weka.core.RevisionUtils;
import weka.core.Summarizable;
import weka.core.Utils;

/**
 *  SplitEvaluator that produces results for a
 * classification scheme on a nominal class attribute, including weighted
 * misclassification costs.
 * 
 * 
 *
 *  Valid options are:
 * 

 *
 * 
 * -W <class name>
 *  The full class name of the classifier.
 *  eg: weka.classifiers.bayes.NaiveBayes
 * 
 *
 *  * -C <index>
 *  The index of the class for which IR statistics
 *  are to be output. (default 1)
 * 
 *
 *  * -I <index>
 *  The index of an attribute to output in the
 *  results. This attribute should identify an
 *  instance in order to know which instances are
 *  in the test set of a cross validation. if 0
 *  no output (default 0).
 * 
 *
 *  * -P
 *  Add target and prediction columns to the result
 *  for each fold.
 * 
 *
 *  * Options specific to classifier weka.classifiers.rules.ZeroR:
 * 
 *
 *  * -D
 *  If set, classifier is run in debug mode and
 *  may output additional info to the console
 * 
 *
 *  * -D <directory>
 *  Name of a directory to search for cost files when loading
 *  costs on demand (default current directory).
 * 
 *
 * 
 *
 * All options after -- will be passed to the classifier.
 *
 * @author Len Trigg ([email protected])
 * @version $Revision: 11323 $
 */
public class CostSensitiveClassifierSplitEvaluator extends
  ClassifierSplitEvaluator {

  /** for serialization */
  static final long serialVersionUID = -8069566663019501276L;

  /**
   * The directory used when loading cost files on demand, null indicates
   * current directory
   */
  protected File m_OnDemandDirectory = new File(System.getProperty("user.dir"));

  /** The length of a result */
  private static final int RESULT_SIZE = 33;

  /**
   * Returns a string describing this split evaluator
   *
   * @return a description of the split evaluator suitable for displaying in the
   *         explorer/experimenter gui
   */
  @Override
  public String globalInfo() {
    return " SplitEvaluator that produces results for a classification scheme "
      + "on a nominal class attribute, including weighted misclassification "
      + "costs.";
  }

  /**
   * Returns an enumeration describing the available options..
   *
   * @return an enumeration of all the available options.
   */
  @Override
  public Enumeration