source: src/main/java/weka/classifiers/RandomizableIteratedSingleClassifierEnhancer.java @ 21

Last change on this file since 21 was 4, checked in by gnappo, 14 years ago

Import di weka.

File size: 3.8 KB
RevLine 
[4]1/*
2 *    This program is free software; you can redistribute it and/or modify
3 *    it under the terms of the GNU General Public License as published by
4 *    the Free Software Foundation; either version 2 of the License, or
5 *    (at your option) any later version.
6 *
7 *    This program is distributed in the hope that it will be useful,
8 *    but WITHOUT ANY WARRANTY; without even the implied warranty of
9 *    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
10 *    GNU General Public License for more details.
11 *
12 *    You should have received a copy of the GNU General Public License
13 *    along with this program; if not, write to the Free Software
14 *    Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
15 */
16
17/*
18 *    RandomizableIteratedSingleClassifierEnhancer.java
19 *    Copyright (C) 2004 University of Waikato, Hamilton, New Zealand
20 *
21 */
22
23package weka.classifiers;
24
25import weka.core.Option;
26import weka.core.Randomizable;
27import weka.core.Utils;
28
29import java.util.Enumeration;
30import java.util.Vector;
31
32/**
33 * Abstract utility class for handling settings common to randomizable
34 * meta classifiers that build an ensemble from a single base learner.
35 *
36 * @author Eibe Frank (eibe@cs.waikato.ac.nz)
37 * @version $Revision: 6041 $
38 */
39public abstract class RandomizableIteratedSingleClassifierEnhancer
40  extends IteratedSingleClassifierEnhancer implements Randomizable {
41
42  /** for serialization */
43  private static final long serialVersionUID = 5063351391524938557L;
44
45  /** The random number seed. */
46  protected int m_Seed = 1;
47
48  /**
49   * Returns an enumeration describing the available options.
50   *
51   * @return an enumeration of all the available options.
52   */
53  public Enumeration listOptions() {
54
55    Vector newVector = new Vector(2);
56
57    newVector.addElement(new Option(
58          "\tRandom number seed.\n"
59          + "\t(default 1)",
60          "S", 1, "-S <num>"));
61
62    Enumeration enu = super.listOptions();
63    while (enu.hasMoreElements()) {
64      newVector.addElement(enu.nextElement());
65    }
66    return newVector.elements();
67  }
68
69  /**
70   * Parses a given list of options. Valid options are:<p>
71   *
72   * -W classname <br>
73   * Specify the full class name of the base learner.<p>
74   *
75   * -I num <br>
76   * Set the number of iterations (default 10). <p>
77   *
78   * -S num <br>
79   * Set the random number seed (default 1). <p>
80   *
81   * Options after -- are passed to the designated classifier.<p>
82   *
83   * @param options the list of options as an array of strings
84   * @exception Exception if an option is not supported
85   */
86  public void setOptions(String[] options) throws Exception {
87
88    String seed = Utils.getOption('S', options);
89    if (seed.length() != 0) {
90      setSeed(Integer.parseInt(seed));
91    } else {
92      setSeed(1);
93    }
94
95    super.setOptions(options);
96  }
97
98  /**
99   * Gets the current settings of the classifier.
100   *
101   * @return an array of strings suitable for passing to setOptions
102   */
103  public String [] getOptions() {
104
105    String [] superOptions = super.getOptions();
106    String [] options = new String [superOptions.length + 2];
107
108    int current = 0;
109    options[current++] = "-S";
110    options[current++] = "" + getSeed();
111
112    System.arraycopy(superOptions, 0, options, current,
113        superOptions.length);
114
115    return options;
116  }
117
118  /**
119   * Returns the tip text for this property
120   * @return tip text for this property suitable for
121   * displaying in the explorer/experimenter gui
122   */
123  public String seedTipText() {
124    return "The random number seed to be used.";
125  }
126
127  /**
128   * Set the seed for random number generation.
129   *
130   * @param seed the seed
131   */
132  public void setSeed(int seed) {
133
134    m_Seed = seed;
135  }
136
137  /**
138   * Gets the seed for the random number generations
139   *
140   * @return the seed for the random number generation
141   */
142  public int getSeed() {
143
144    return m_Seed;
145  }
146}
Note: See TracBrowser for help on using the repository browser.