1 | /* |
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2 | * This program is free software; you can redistribute it and/or modify |
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3 | * it under the terms of the GNU General Public License as published by |
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4 | * the Free Software Foundation; either version 2 of the License, or |
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5 | * (at your option) any later version. |
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6 | * |
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7 | * This program is distributed in the hope that it will be useful, |
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8 | * but WITHOUT ANY WARRANTY; without even the implied warranty of |
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9 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
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10 | * GNU General Public License for more details. |
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11 | * |
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12 | * You should have received a copy of the GNU General Public License |
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13 | * along with this program; if not, write to the Free Software |
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14 | * Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA. |
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15 | */ |
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16 | |
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17 | /* |
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18 | * RegressionGenerator.java |
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19 | * Copyright (C) 2005 University of Waikato, Hamilton, New Zealand |
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20 | * |
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21 | */ |
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22 | |
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23 | package weka.datagenerators; |
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24 | |
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25 | import weka.core.Option; |
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26 | import weka.core.Utils; |
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27 | import weka.datagenerators.DataGenerator; |
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28 | |
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29 | import java.util.Enumeration; |
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30 | import java.util.Vector; |
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31 | |
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32 | /** |
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33 | * Abstract class for data generators for regression classifiers. <p/> |
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34 | * |
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35 | * Example usage as the main of a datagenerator called RandomGenerator: |
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36 | * <pre> |
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37 | * public static void main(String[] args) { |
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38 | * try { |
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39 | * DataGenerator.makeData(new RandomGenerator(), args); |
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40 | * } |
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41 | * catch (Exception e) { |
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42 | * e.printStackTrace(); |
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43 | * System.err.println(e.getMessage()); |
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44 | * } |
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45 | * } |
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46 | * </pre> |
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47 | * |
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48 | * @author FracPete (fracpete at waikato dot ac dot nz) |
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49 | * @version $Revision: 1.3 $ |
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50 | */ |
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51 | public abstract class RegressionGenerator |
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52 | extends DataGenerator { |
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53 | |
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54 | /** for serialization */ |
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55 | private static final long serialVersionUID = 3073254041275658221L; |
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56 | |
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57 | /** Number of instances*/ |
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58 | protected int m_NumExamples; |
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59 | |
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60 | /** |
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61 | * initializes the generator with default values |
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62 | */ |
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63 | public RegressionGenerator() { |
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64 | super(); |
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65 | |
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66 | setNumExamples(defaultNumExamples()); |
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67 | } |
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68 | |
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69 | /** |
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70 | * Returns an enumeration describing the available options. |
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71 | * |
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72 | * @return an enumeration of all the available options. |
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73 | */ |
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74 | public Enumeration listOptions() { |
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75 | Vector result = enumToVector(super.listOptions()); |
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76 | |
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77 | result.addElement(new Option( |
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78 | "\tThe number of examples to generate (default " |
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79 | + defaultNumExamples() + ")", |
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80 | "n", 1, "-n <num>")); |
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81 | |
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82 | return result.elements(); |
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83 | } |
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84 | |
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85 | /** |
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86 | * Sets the options. |
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87 | * |
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88 | * @param options the options |
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89 | * @throws Exception if invalid option |
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90 | */ |
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91 | public void setOptions(String[] options) throws Exception { |
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92 | String tmpStr; |
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93 | |
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94 | super.setOptions(options); |
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95 | |
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96 | tmpStr = Utils.getOption('n', options); |
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97 | if (tmpStr.length() != 0) |
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98 | setNumExamples(Integer.parseInt(tmpStr)); |
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99 | else |
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100 | setNumExamples(defaultNumExamples()); |
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101 | } |
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102 | |
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103 | /** |
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104 | * Gets the current settings of the classifier. |
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105 | * |
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106 | * @return an array of strings suitable for passing to setOptions |
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107 | */ |
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108 | public String[] getOptions() { |
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109 | Vector result; |
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110 | String[] options; |
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111 | int i; |
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112 | |
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113 | result = new Vector(); |
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114 | options = super.getOptions(); |
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115 | for (i = 0; i < options.length; i++) |
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116 | result.add(options[i]); |
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117 | |
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118 | result.add("-n"); |
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119 | result.add("" + getNumExamples()); |
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120 | |
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121 | return (String[]) result.toArray(new String[result.size()]); |
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122 | } |
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123 | |
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124 | /** |
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125 | * returns the default number of examples |
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126 | * |
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127 | * @return the default number of examples |
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128 | */ |
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129 | protected int defaultNumExamples() { |
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130 | return 100; |
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131 | } |
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132 | |
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133 | /** |
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134 | * Sets the number of examples, given by option. |
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135 | * @param numExamples the new number of examples |
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136 | */ |
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137 | public void setNumExamples(int numExamples) { |
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138 | m_NumExamples = numExamples; |
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139 | } |
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140 | |
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141 | /** |
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142 | * Gets the number of examples, given by option. |
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143 | * @return the number of examples, given by option |
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144 | */ |
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145 | public int getNumExamples() { |
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146 | return m_NumExamples; |
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147 | } |
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148 | |
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149 | /** |
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150 | * Returns the tip text for this property |
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151 | * |
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152 | * @return tip text for this property suitable for |
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153 | * displaying in the explorer/experimenter gui |
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154 | */ |
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155 | public String numExamplesTipText() { |
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156 | return "The number of examples to generate."; |
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157 | } |
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158 | } |
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