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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.
/*
* 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.
*/
/*
* CostSensitiveClassifierSplitEvaluator.java
* Copyright (C) 2002 University of Waikato, Hamilton, New Zealand
*
*/
package weka.experiment;
import weka.classifiers.Classifier;
import weka.classifiers.CostMatrix;
import weka.classifiers.Evaluation;
import weka.core.AdditionalMeasureProducer;
import weka.core.Attribute;
import weka.core.Instance;
import weka.core.Instances;
import weka.core.Option;
import weka.core.RevisionUtils;
import weka.core.Summarizable;
import weka.core.Utils;
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.Enumeration;
import java.util.Vector;
/**
* 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: 7516 $
*/
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 = 31;
/**
* Returns a string describing this split evaluator
* @return a description of the split evaluator suitable for
* displaying in the explorer/experimenter gui
*/
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.
*/
public Enumeration listOptions() {
Vector newVector = new Vector(1);
Enumeration enu = super.listOptions();
while (enu.hasMoreElements()) {
newVector.addElement(enu.nextElement());
}
newVector.addElement(new Option(
"\tName of a directory to search for cost files when loading\n"
+"\tcosts on demand (default current directory).",
"D", 1, "-D "));
return newVector.elements();
}
/**
* Parses a given list of options.
*
* 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.
*
* @param options the list of options as an array of strings
* @throws Exception if an option is not supported
*/
public void setOptions(String[] options) throws Exception {
String demandDir = Utils.getOption('D', options);
if (demandDir.length() != 0) {
setOnDemandDirectory(new File(demandDir));
}
super.setOptions(options);
}
/**
* Gets the current settings of the Classifier.
*
* @return an array of strings suitable for passing to setOptions
*/
public String [] getOptions() {
String [] superOptions = super.getOptions();
String [] options = new String [superOptions.length + 3];
int current = 0;
options[current++] = "-D";
options[current++] = "" + getOnDemandDirectory();
System.arraycopy(superOptions, 0, options, current,
superOptions.length);
current += superOptions.length;
while (current < options.length) {
options[current++] = "";
}
return options;
}
/**
* Returns the tip text for this property
* @return tip text for this property suitable for
* displaying in the explorer/experimenter gui
*/
public String onDemandDirectoryTipText() {
return "The directory to look in for cost files. This directory will be "
+"searched for cost files when loading on demand.";
}
/**
* Returns the directory that will be searched for cost files when
* loading on demand.
*
* @return The cost file search directory.
*/
public File getOnDemandDirectory() {
return m_OnDemandDirectory;
}
/**
* Sets the directory that will be searched for cost files when
* loading on demand.
*
* @param newDir The cost file search directory.
*/
public void setOnDemandDirectory(File newDir) {
if (newDir.isDirectory()) {
m_OnDemandDirectory = newDir;
} else {
m_OnDemandDirectory = new File(newDir.getParent());
}
}
/**
* Gets the data types of each of the result columns produced for a
* single run. The number of result fields must be constant
* for a given SplitEvaluator.
*
* @return an array containing objects of the type of each result column.
* The objects should be Strings, or Doubles.
*/
public Object [] getResultTypes() {
int addm = (m_AdditionalMeasures != null)
? m_AdditionalMeasures.length
: 0;
Object [] resultTypes = new Object[RESULT_SIZE+addm];
Double doub = new Double(0);
int current = 0;
resultTypes[current++] = doub;
resultTypes[current++] = doub;
resultTypes[current++] = doub;
resultTypes[current++] = doub;
resultTypes[current++] = doub;
resultTypes[current++] = doub;
resultTypes[current++] = doub;
resultTypes[current++] = doub;
resultTypes[current++] = doub;
resultTypes[current++] = doub;
resultTypes[current++] = doub;
resultTypes[current++] = doub;
resultTypes[current++] = doub;
resultTypes[current++] = doub;
resultTypes[current++] = doub;
resultTypes[current++] = doub;
resultTypes[current++] = doub;
resultTypes[current++] = doub;
resultTypes[current++] = doub;
resultTypes[current++] = doub;
resultTypes[current++] = doub;
resultTypes[current++] = doub;
resultTypes[current++] = doub;
// Timing stats
resultTypes[current++] = doub;
resultTypes[current++] = doub;
resultTypes[current++] = doub;
resultTypes[current++] = doub;
// sizes
resultTypes[current++] = doub;
resultTypes[current++] = doub;
resultTypes[current++] = doub;
resultTypes[current++] = "";
// add any additional measures
for (int i=0;i classifier";
}
return result + m_Template.getClass().getName() + " "
+ m_ClassifierOptions + "(version " + m_ClassifierVersion + ")";
}
/**
* Returns the revision string.
*
* @return the revision
*/
public String getRevision() {
return RevisionUtils.extract("$Revision: 7516 $");
}
} // CostSensitiveClassifierSplitEvaluator
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