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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 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.
 */

/*
 *    SingleClassifierEnhancer.java
 *    Copyright (C) 2004 University of Waikato, Hamilton, New Zealand
 *
 */

package weka.classifiers;

import weka.classifiers.rules.ZeroR;
import weka.core.Capabilities;
import weka.core.Option;
import weka.core.OptionHandler;
import weka.core.Utils;
import weka.core.Capabilities.Capability;

import java.util.Enumeration;
import java.util.Vector;

/**
 * Abstract utility class for handling settings common to meta
 * classifiers that use a single base learner.  
 *
 * @author Eibe Frank ([email protected])
 * @version $Revision: 5536 $
 */
public abstract class SingleClassifierEnhancer extends Classifier {

  /** for serialization */
  private static final long serialVersionUID = -3665885256363525164L;

  /** The base classifier to use */
  protected Classifier m_Classifier = new ZeroR();

  /**
   * String describing default classifier.
   */
  protected String defaultClassifierString() {
    
    return "weka.classifiers.rules.ZeroR";
  }

  /**
   * Returns an enumeration describing the available options.
   *
   * @return an enumeration of all the available options.
   */
  public Enumeration listOptions() {

    Vector newVector = new Vector(3);

    Enumeration enu = super.listOptions();
    while (enu.hasMoreElements()) {
      newVector.addElement(enu.nextElement());
    }

    newVector.addElement(new Option(
	      "\tFull name of base classifier.\n"
	      + "\t(default: " + defaultClassifierString() +")",
	      "W", 1, "-W"));

    newVector.addElement(new Option(
	     "",
	     "", 0, "\nOptions specific to classifier "
	     + m_Classifier.getClass().getName() + ":"));
    enu = ((OptionHandler)m_Classifier).listOptions();
    while (enu.hasMoreElements()) {
      newVector.addElement(enu.nextElement());
    }

    return newVector.elements();
  }

  /**
   * Parses a given list of options. Valid options are:

* * -W classname
* Specify the full class name of the base learner.

* * Options after -- are passed to the designated classifier.

* * @param options the list of options as an array of strings * @exception Exception if an option is not supported */ public void setOptions(String[] options) throws Exception { super.setOptions(options); String classifierName = Utils.getOption('W', options); if (classifierName.length() > 0) { // This is just to set the classifier in case the option // parsing fails. setClassifier(Classifier.forName(classifierName, null)); setClassifier(Classifier.forName(classifierName, Utils.partitionOptions(options))); } else { // This is just to set the classifier in case the option // parsing fails. setClassifier(Classifier.forName(defaultClassifierString(), null)); setClassifier(Classifier.forName(defaultClassifierString(), Utils.partitionOptions(options))); } } /** * Gets the current settings of the Classifier. * * @return an array of strings suitable for passing to setOptions */ public String [] getOptions() { String [] classifierOptions = ((OptionHandler)m_Classifier).getOptions(); int extraOptionsLength = classifierOptions.length; if (extraOptionsLength > 0) { extraOptionsLength++; // for the double hyphen } String [] superOptions = super.getOptions(); String [] options = new String [superOptions.length + extraOptionsLength + 2]; int current = 0; options[current++] = "-W"; options[current++] = getClassifier().getClass().getName(); System.arraycopy(superOptions, 0, options, current, superOptions.length); current += superOptions.length; if (classifierOptions.length > 0) { options[current++] = "--"; System.arraycopy(classifierOptions, 0, options, current, classifierOptions.length); } 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 classifierTipText() { return "The base classifier to be used."; } /** * Returns default capabilities of the base classifier. * * @return the capabilities of the base classifier */ public Capabilities getCapabilities() { Capabilities result; if (getClassifier() != null) { result = getClassifier().getCapabilities(); } else { result = new Capabilities(this); result.disableAll(); } // set dependencies for (Capability cap: Capability.values()) result.enableDependency(cap); result.setOwner(this); return result; } /** * Set the base learner. * * @param newClassifier the classifier to use. */ public void setClassifier(Classifier newClassifier) { m_Classifier = newClassifier; } /** * Get the classifier used as the base learner. * * @return the classifier used as the classifier */ public Classifier getClassifier() { return m_Classifier; } /** * Gets the classifier specification string, which contains the class name of * the classifier and any options to the classifier * * @return the classifier string */ protected String getClassifierSpec() { Classifier c = getClassifier(); return c.getClass().getName() + " " + Utils.joinOptions(((OptionHandler)c).getOptions()); } }





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