source: src/main/java/weka/classifiers/RandomizableParallelIteratedSingleClassifierEnhancer.java @ 6

Last change on this file since 6 was 4, checked in by gnappo, 14 years ago

Import di weka.

File size: 3.8 KB
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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 *    RandomizableParallelIteratedSingleClassifierEnhancer.java
19 *    Copyright (C) 2009 University of Waikato, Hamilton, New Zealand
20 *
21 */
22
23package weka.classifiers;
24
25import java.util.Enumeration;
26import java.util.Vector;
27
28import weka.core.Option;
29import weka.core.Utils;
30
31/**
32 * Abstract utility class for handling settings common to randomizable
33 * meta classifiers that build an ensemble in parallel from a single base
34 * learner.
35 *
36 * @author Mark Hall (mhall{[at]}pentaho{[dot]}com)
37 * @version $Revision: 6041 $
38 */
39public abstract class RandomizableParallelIteratedSingleClassifierEnhancer
40    extends ParallelIteratedSingleClassifierEnhancer {
41
42  /**
43   * For serialization
44   */
45  private static final long serialVersionUID = 1298141000373615374L;
46
47  /** The random number seed. */
48  protected int m_Seed = 1;
49
50  /**
51   * Returns an enumeration describing the available options.
52   *
53   * @return an enumeration of all the available options.
54   */
55  public Enumeration listOptions() {
56
57    Vector newVector = new Vector(2);
58
59    newVector.addElement(new Option(
60              "\tRandom number seed.\n"
61              + "\t(default 1)",
62              "S", 1, "-S <num>"));
63
64    Enumeration enu = super.listOptions();
65    while (enu.hasMoreElements()) {
66      newVector.addElement(enu.nextElement());
67    }
68    return newVector.elements();
69  }
70
71  /**
72   * Parses a given list of options. Valid options are:<p>
73   *
74   * -W classname <br>
75   * Specify the full class name of the base learner.<p>
76   *
77   * -I num <br>
78   * Set the number of iterations (default 10). <p>
79   *
80   * -S num <br>
81   * Set the random number seed (default 1). <p>
82   *
83   * Options after -- are passed to the designated classifier.<p>
84   *
85   * @param options the list of options as an array of strings
86   * @exception Exception if an option is not supported
87   */
88  public void setOptions(String[] options) throws Exception {
89
90    String seed = Utils.getOption('S', options);
91    if (seed.length() != 0) {
92      setSeed(Integer.parseInt(seed));
93    } else {
94      setSeed(1);
95    }
96
97    super.setOptions(options);
98  }
99
100  /**
101   * Gets the current settings of the classifier.
102   *
103   * @return an array of strings suitable for passing to setOptions
104   */
105  public String [] getOptions() {
106
107    String [] superOptions = super.getOptions();
108    String [] options = new String [superOptions.length + 2];
109
110    int current = 0;
111    options[current++] = "-S";
112    options[current++] = "" + getSeed();
113
114    System.arraycopy(superOptions, 0, options, current,
115                     superOptions.length);
116
117    return options;
118  }
119
120  /**
121   * Returns the tip text for this property
122   * @return tip text for this property suitable for
123   * displaying in the explorer/experimenter gui
124   */
125  public String seedTipText() {
126    return "The random number seed to be used.";
127  }
128
129  /**
130   * Set the seed for random number generation.
131   *
132   * @param seed the seed
133   */
134  public void setSeed(int seed) {
135
136    m_Seed = seed;
137  }
138
139  /**
140   * Gets the seed for the random number generations
141   *
142   * @return the seed for the random number generation
143   */
144  public int getSeed() {
145
146    return m_Seed;
147  }
148
149}
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