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The Waikato Environment for Knowledge Analysis (WEKA), a machine learning workbench. This version represents the developer version, the "bleeding edge" of development, you could say. New functionality gets added to this version.

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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 .
 */

/*
 *    RandomizableSingleClassifierEnhancer.java
 *    Copyright (C) 2004-2012 University of Waikato, Hamilton, New Zealand
 *
 */

package weka.classifiers;

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

import weka.core.Option;
import weka.core.Randomizable;
import weka.core.Utils;

/**
 * Abstract utility class for handling settings common to randomizable
 * meta classifiers that build an ensemble from a single base learner.
 *
 * @author Eibe Frank ([email protected])
 * @version $Revision: 10141 $
 */
public abstract class RandomizableSingleClassifierEnhancer
  extends SingleClassifierEnhancer implements Randomizable {

  /** for serialization */
  private static final long serialVersionUID = 558286687096157160L;

  /** The random number seed. */
  protected int m_Seed = 1;

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

* * @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 { String seed = Utils.getOption('S', options); if (seed.length() != 0) { setSeed(Integer.parseInt(seed)); } else { setSeed(1); } super.setOptions(options); } /** * Gets the current settings of the classifier. * * @return an array of strings suitable for passing to setOptions */ public String [] getOptions() { Vector options = new Vector(); options.add("-S"); options.add("" + getSeed()); Collections.addAll(options, super.getOptions()); return options.toArray(new String[0]); } /** * Returns the tip text for this property * @return tip text for this property suitable for * displaying in the explorer/experimenter gui */ public String seedTipText() { return "The random number seed to be used."; } /** * Set the seed for random number generation. * * @param seed the seed */ public void setSeed(int seed) { m_Seed = seed; } /** * Gets the seed for the random number generations * * @return the seed for the random number generation */ public int getSeed() { return m_Seed; } }





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