1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2008 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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4 | *
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5 | * This file is part of HeuristicLab.
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6 | *
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7 | * HeuristicLab is free software: you can redistribute it and/or modify
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8 | * it under the terms of the GNU General Public License as published by
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9 | * the Free Software Foundation, either version 3 of the License, or
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10 | * (at your option) any later version.
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11 | *
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12 | * HeuristicLab is distributed in the hope that it will be useful,
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13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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15 | * GNU General Public License for more details.
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16 | *
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17 | * You should have received a copy of the GNU General Public License
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18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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19 | */
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20 | #endregion
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21 |
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22 | using System;
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23 | using System.Collections.Generic;
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24 | using System.Linq;
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25 | using System.Text;
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26 | using HeuristicLab.Core;
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27 | using System.Xml;
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28 | using System.Diagnostics;
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29 | using HeuristicLab.DataAnalysis;
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30 | using HeuristicLab.Data;
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31 | using HeuristicLab.Operators;
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32 | using HeuristicLab.GP.StructureIdentification;
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33 | using HeuristicLab.Logging;
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34 | using HeuristicLab.Operators.Programmable;
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35 | using HeuristicLab.Modeling;
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36 | using HeuristicLab.Random;
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37 | using HeuristicLab.Selection;
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38 |
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39 | namespace HeuristicLab.SupportVectorMachines {
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40 | public class SupportVectorRegression : ItemBase, IEditable, IAlgorithm {
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41 |
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42 | public string Name { get { return "SupportVectorRegression"; } }
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43 | public string Description { get { return "TODO"; } }
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44 |
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45 | private SequentialEngine.SequentialEngine engine;
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46 | public IEngine Engine {
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47 | get { return engine; }
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48 | }
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49 |
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50 | public Dataset Dataset {
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51 | get { return ProblemInjector.GetVariableValue<Dataset>("Dataset", null, false); }
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52 | set { ProblemInjector.GetVariable("Dataset").Value = value; }
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53 | }
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54 |
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55 | public int TargetVariable {
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56 | get { return ProblemInjector.GetVariableValue<IntData>("TargetVariable", null, false).Data; }
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57 | set { ProblemInjector.GetVariableValue<IntData>("TargetVariable", null, false).Data = value; }
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58 | }
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59 |
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60 | public IOperator ProblemInjector {
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61 | get {
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62 | IOperator main = GetMainOperator();
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63 | return main.SubOperators[1];
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64 | }
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65 | set {
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66 | IOperator main = GetMainOperator();
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67 | main.RemoveSubOperator(1);
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68 | main.AddSubOperator(value, 1);
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69 | }
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70 | }
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71 |
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72 | public IModel Model {
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73 | get {
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74 | if (!engine.Terminated) throw new InvalidOperationException("The algorithm is still running. Wait until the algorithm is terminated to retrieve the result.");
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75 | IScope bestModelScope = engine.GlobalScope.SubScopes[0];
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76 | return CreateSVMModel(bestModelScope);
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77 | }
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78 | }
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79 |
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80 | public DoubleArrayData NuList {
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81 | get { return GetVariableInjector().GetVariable("NuList").GetValue<DoubleArrayData>(); }
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82 | set { GetVariableInjector().GetVariable("NuList").Value = value; }
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83 | }
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84 |
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85 | public int MaxNuIndex {
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86 | get { return GetVariableInjector().GetVariable("MaxNuIndex").GetValue<IntData>().Data; }
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87 | set { GetVariableInjector().GetVariable("MaxNuIndex").GetValue<IntData>().Data = value; }
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88 | }
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89 |
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90 | public DoubleArrayData CostList {
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91 | get { return GetVariableInjector().GetVariable("CostList").GetValue<DoubleArrayData>(); }
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92 | set { GetVariableInjector().GetVariable("CostList").Value = value; }
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93 | }
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94 |
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95 | public int MaxCostIndex {
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96 | get { return GetVariableInjector().GetVariable("MaxCostIndex").GetValue<IntData>().Data; }
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97 | set { GetVariableInjector().GetVariable("MaxCostIndex").GetValue<IntData>().Data = value; }
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98 | }
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99 |
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100 | public SupportVectorRegression() {
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101 | engine = new SequentialEngine.SequentialEngine();
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102 | CombinedOperator algo = CreateAlgorithm();
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103 | engine.OperatorGraph.AddOperator(algo);
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104 | engine.OperatorGraph.InitialOperator = algo;
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105 | MaxCostIndex = CostList.Data.Length;
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106 | MaxNuIndex = NuList.Data.Length;
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107 | }
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108 |
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109 | private CombinedOperator CreateAlgorithm() {
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110 | CombinedOperator algo = new CombinedOperator();
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111 | algo.Name = "SupportVectorRegression";
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112 | IOperator main = CreateMainLoop();
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113 | algo.OperatorGraph.AddOperator(main);
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114 | algo.OperatorGraph.InitialOperator = main;
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115 | return algo;
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116 | }
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117 |
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118 | private IOperator CreateMainLoop() {
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119 | SequentialProcessor main = new SequentialProcessor();
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120 | main.AddSubOperator(CreateGlobalInjector());
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121 | main.AddSubOperator(new ProblemInjector());
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122 | main.AddSubOperator(new RandomInjector());
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123 |
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124 | SubScopesCreater modelScopeCreator = new SubScopesCreater();
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125 | modelScopeCreator.GetVariableInfo("SubScopes").Local = true;
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126 | modelScopeCreator.AddVariable(new HeuristicLab.Core.Variable("SubScopes", new IntData(1)));
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127 | main.AddSubOperator(modelScopeCreator);
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128 |
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129 | SequentialSubScopesProcessor seqSubScopesProc = new SequentialSubScopesProcessor();
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130 | IOperator modelProcessor = CreateModelProcessor();
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131 | seqSubScopesProc.AddSubOperator(modelProcessor);
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132 | main.AddSubOperator(seqSubScopesProc);
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133 |
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134 | SequentialProcessor nuLoop = new SequentialProcessor();
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135 | nuLoop.Name = "NuLoop";
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136 |
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137 | IOperator costCounter = CreateCounter("Cost");
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138 | IOperator costComparator = CreateComparator("Cost");
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139 | nuLoop.AddSubOperator(costCounter);
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140 | nuLoop.AddSubOperator(costComparator);
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141 | ConditionalBranch costBranch = new ConditionalBranch();
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142 | costBranch.Name = "IfValidCostIndex";
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143 | costBranch.GetVariableInfo("Condition").ActualName = "RepeatCostLoop";
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144 |
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145 | // build cost loop
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146 | SequentialProcessor costLoop = new SequentialProcessor();
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147 | costLoop.Name = "CostLoop";
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148 | costLoop.AddSubOperator(modelScopeCreator);
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149 | SequentialSubScopesProcessor subScopesProcessor = new SequentialSubScopesProcessor();
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150 | costLoop.AddSubOperator(subScopesProcessor);
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151 | subScopesProcessor.AddSubOperator(new EmptyOperator());
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152 | subScopesProcessor.AddSubOperator(modelProcessor);
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153 |
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154 | Sorter sorter = new Sorter();
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155 | sorter.GetVariableInfo("Value").ActualName = "ValidationQuality";
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156 | sorter.GetVariableInfo("Descending").Local = true;
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157 | sorter.AddVariable(new Variable("Descending", new BoolData(false)));
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158 | costLoop.AddSubOperator(sorter);
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159 |
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160 | LeftSelector selector = new LeftSelector();
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161 | selector.GetVariableInfo("Selected").Local = true;
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162 | selector.AddVariable(new Variable("Selected", new IntData(1)));
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163 | costLoop.AddSubOperator(selector);
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164 |
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165 | RightReducer reducer = new RightReducer();
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166 | costLoop.AddSubOperator(reducer);
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167 |
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168 | costLoop.AddSubOperator(costCounter);
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169 | costLoop.AddSubOperator(costComparator);
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170 |
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171 | costBranch.AddSubOperator(costLoop);
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172 | costLoop.AddSubOperator(costBranch);
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173 |
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174 | nuLoop.AddSubOperator(costBranch);
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175 | nuLoop.AddSubOperator(CreateResetOperator("CostIndex"));
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176 |
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177 | nuLoop.AddSubOperator(CreateCounter("Nu"));
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178 | nuLoop.AddSubOperator(CreateComparator("Nu"));
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179 |
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180 | ConditionalBranch nuBranch = new ConditionalBranch();
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181 | nuBranch.Name = "NuLoop";
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182 | nuBranch.GetVariableInfo("Condition").ActualName = "RepeatNuLoop";
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183 | nuBranch.AddSubOperator(nuLoop);
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184 | nuLoop.AddSubOperator(nuBranch);
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185 |
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186 | main.AddSubOperator(nuLoop);
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187 | main.AddSubOperator(CreateModelAnalyser());
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188 | return main;
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189 | }
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190 |
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191 | private IOperator CreateModelProcessor() {
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192 | SequentialProcessor modelProcessor = new SequentialProcessor();
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193 | modelProcessor.AddSubOperator(CreateSetNextParameterValueOperator("Nu"));
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194 | modelProcessor.AddSubOperator(CreateSetNextParameterValueOperator("Cost"));
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195 |
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196 | SupportVectorCreator modelCreator = new SupportVectorCreator();
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197 | modelCreator.GetVariableInfo("SamplesStart").ActualName = "TrainingSamplesStart";
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198 | modelCreator.GetVariableInfo("SamplesEnd").ActualName = "TrainingSamplesEnd";
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199 | modelCreator.GetVariableInfo("SVMCost").ActualName = "Cost";
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200 | modelCreator.GetVariableInfo("SVMGamma").ActualName = "Gamma";
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201 | modelCreator.GetVariableInfo("SVMKernelType").ActualName = "KernelType";
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202 | modelCreator.GetVariableInfo("SVMModel").ActualName = "Model";
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203 | modelCreator.GetVariableInfo("SVMNu").ActualName = "Nu";
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204 | modelCreator.GetVariableInfo("SVMType").ActualName = "Type";
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205 |
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206 | modelProcessor.AddSubOperator(modelCreator);
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207 | CombinedOperator trainingEvaluator = (CombinedOperator)CreateEvaluator("Training");
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208 | trainingEvaluator.OperatorGraph.InitialOperator.SubOperators[1].GetVariableInfo("MSE").ActualName = "Quality";
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209 | modelProcessor.AddSubOperator(trainingEvaluator);
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210 | modelProcessor.AddSubOperator(CreateEvaluator("Validation"));
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211 | modelProcessor.AddSubOperator(CreateEvaluator("Test"));
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212 |
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213 | DataCollector collector = new DataCollector();
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214 | collector.GetVariableInfo("Values").ActualName = "Log";
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215 | ((ItemList<StringData>)collector.GetVariable("VariableNames").Value).Add(new StringData("Nu"));
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216 | ((ItemList<StringData>)collector.GetVariable("VariableNames").Value).Add(new StringData("Cost"));
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217 | ((ItemList<StringData>)collector.GetVariable("VariableNames").Value).Add(new StringData("ValidationQuality"));
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218 | modelProcessor.AddSubOperator(collector);
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219 | return modelProcessor;
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220 | }
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221 |
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222 | private IOperator CreateComparator(string p) {
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223 | LessThanComparator comparator = new LessThanComparator();
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224 | comparator.Name = p + "IndexComparator";
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225 | comparator.GetVariableInfo("LeftSide").ActualName = p + "Index";
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226 | comparator.GetVariableInfo("RightSide").ActualName = "Max" + p + "Index";
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227 | comparator.GetVariableInfo("Result").ActualName = "Repeat" + p + "Loop";
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228 | return comparator;
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229 | }
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230 |
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231 | private IOperator CreateCounter(string p) {
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232 | Counter c = new Counter();
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233 | c.GetVariableInfo("Value").ActualName = p + "Index";
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234 | c.Name = p + "Counter";
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235 | return c;
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236 | }
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237 |
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238 | private IOperator CreateEvaluator(string p) {
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239 | CombinedOperator op = new CombinedOperator();
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240 | op.Name = p + "Evaluator";
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241 | SequentialProcessor seqProc = new SequentialProcessor();
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242 |
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243 | SupportVectorEvaluator evaluator = new SupportVectorEvaluator();
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244 | evaluator.Name = p + "SimpleEvaluator";
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245 | evaluator.GetVariableInfo("SVMModel").ActualName = "Model";
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246 | evaluator.GetVariableInfo("SamplesStart").ActualName = p + "SamplesStart";
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247 | evaluator.GetVariableInfo("SamplesEnd").ActualName = p + "SamplesEnd";
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248 | evaluator.GetVariableInfo("Values").ActualName = p + "Values";
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249 | SimpleMSEEvaluator mseEvaluator = new SimpleMSEEvaluator();
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250 | mseEvaluator.Name = p + "MseEvaluator";
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251 | mseEvaluator.GetVariableInfo("Values").ActualName = p + "Values";
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252 | mseEvaluator.GetVariableInfo("MSE").ActualName = p + "Quality";
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253 | SimpleR2Evaluator r2Evaluator = new SimpleR2Evaluator();
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254 | r2Evaluator.Name = p + "R2Evaluator";
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255 | r2Evaluator.GetVariableInfo("Values").ActualName = p + "Values";
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256 | r2Evaluator.GetVariableInfo("R2").ActualName = p + "R2";
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257 | SimpleMeanAbsolutePercentageErrorEvaluator mapeEvaluator = new SimpleMeanAbsolutePercentageErrorEvaluator();
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258 | mapeEvaluator.Name = p + "MAPEEvaluator";
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259 | mapeEvaluator.GetVariableInfo("Values").ActualName = p + "Values";
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260 | mapeEvaluator.GetVariableInfo("MAPE").ActualName = p + "MAPE";
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261 | SimpleMeanAbsolutePercentageOfRangeErrorEvaluator mapreEvaluator = new SimpleMeanAbsolutePercentageOfRangeErrorEvaluator();
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262 | mapreEvaluator.Name = p + "MAPREEvaluator";
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263 | mapreEvaluator.GetVariableInfo("Values").ActualName = p + "Values";
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264 | mapreEvaluator.GetVariableInfo("MAPRE").ActualName = p + "MAPRE";
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265 | SimpleVarianceAccountedForEvaluator vafEvaluator = new SimpleVarianceAccountedForEvaluator();
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266 | vafEvaluator.Name = p + "VAFEvaluator";
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267 | vafEvaluator.GetVariableInfo("Values").ActualName = p + "Values";
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268 | vafEvaluator.GetVariableInfo("VAF").ActualName = p + "VAF";
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269 |
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270 | seqProc.AddSubOperator(evaluator);
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271 | seqProc.AddSubOperator(mseEvaluator);
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272 | seqProc.AddSubOperator(r2Evaluator);
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273 | seqProc.AddSubOperator(mapeEvaluator);
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274 | seqProc.AddSubOperator(mapreEvaluator);
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275 | seqProc.AddSubOperator(vafEvaluator);
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276 |
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277 | op.OperatorGraph.AddOperator(seqProc);
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278 | op.OperatorGraph.InitialOperator = seqProc;
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279 | return op;
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280 | }
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281 |
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282 | private IOperator CreateSetNextParameterValueOperator(string paramName) {
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283 | ProgrammableOperator progOp = new ProgrammableOperator();
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284 | progOp.Name = "SetNext" + paramName;
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285 | progOp.RemoveVariableInfo("Result");
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286 | progOp.AddVariableInfo(new VariableInfo("Value", "Value", typeof(DoubleData), VariableKind.New));
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287 | progOp.AddVariableInfo(new VariableInfo("ValueIndex", "ValueIndex", typeof(IntData), VariableKind.In));
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288 | progOp.AddVariableInfo(new VariableInfo("ValueList", "ValueList", typeof(DoubleArrayData), VariableKind.In));
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289 | progOp.Code =
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290 | @"
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291 | Value.Data = ValueList.Data[ValueIndex.Data];
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292 | ";
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293 |
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294 | progOp.GetVariableInfo("Value").ActualName = paramName;
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295 | progOp.GetVariableInfo("ValueIndex").ActualName = paramName + "Index";
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296 | progOp.GetVariableInfo("ValueList").ActualName = paramName + "List";
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297 | return progOp;
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298 | }
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299 |
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300 | private IOperator CreateResetOperator(string paramName) {
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301 | ProgrammableOperator progOp = new ProgrammableOperator();
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302 | progOp.Name = "Reset" + paramName;
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303 | progOp.RemoveVariableInfo("Result");
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304 | progOp.AddVariableInfo(new VariableInfo("Value", "Value", typeof(IntData), VariableKind.In | VariableKind.Out));
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305 | progOp.Code = "Value.Data = -1;";
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306 | progOp.GetVariableInfo("Value").ActualName = paramName;
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307 | return progOp;
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308 | }
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309 |
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310 | private IOperator CreateGlobalInjector() {
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311 | VariableInjector injector = new VariableInjector();
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312 | injector.AddVariable(new HeuristicLab.Core.Variable("CostIndex", new IntData(0)));
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313 | injector.AddVariable(new HeuristicLab.Core.Variable("CostList", new DoubleArrayData(new double[] { 0.1, 0.25, 0.5, 1.0, 2.0, 4.0, 8.0 })));
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314 | injector.AddVariable(new HeuristicLab.Core.Variable("MaxCostIndex", new IntData()));
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315 | injector.AddVariable(new HeuristicLab.Core.Variable("NuIndex", new IntData(0)));
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316 | injector.AddVariable(new HeuristicLab.Core.Variable("NuList", new DoubleArrayData(new double[] { 0.01, 0.05, 0.1, 0.5 })));
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317 | injector.AddVariable(new HeuristicLab.Core.Variable("MaxNuIndex", new IntData()));
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318 | injector.AddVariable(new HeuristicLab.Core.Variable("Log", new ItemList()));
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319 | injector.AddVariable(new HeuristicLab.Core.Variable("Gamma", new DoubleData(1)));
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320 | injector.AddVariable(new HeuristicLab.Core.Variable("KernelType", new StringData("RBF")));
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321 | injector.AddVariable(new HeuristicLab.Core.Variable("Type", new StringData("NU_SVR")));
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322 |
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323 | return injector;
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324 | }
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325 |
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326 | private IOperator CreateModelAnalyser() {
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327 | CombinedOperator modelAnalyser = new CombinedOperator();
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328 | modelAnalyser.Name = "Model Analyzer";
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329 | SequentialSubScopesProcessor seqSubScopeProc = new SequentialSubScopesProcessor();
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330 | SequentialProcessor seqProc = new SequentialProcessor();
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331 | VariableEvaluationImpactCalculator evalImpactCalc = new VariableEvaluationImpactCalculator();
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332 | evalImpactCalc.GetVariableInfo("SVMModel").ActualName = "Model";
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333 | VariableQualityImpactCalculator qualImpactCalc = new VariableQualityImpactCalculator();
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334 | qualImpactCalc.GetVariableInfo("SVMModel").ActualName = "Model";
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335 |
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336 | seqProc.AddSubOperator(evalImpactCalc);
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337 | seqProc.AddSubOperator(qualImpactCalc);
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338 | seqSubScopeProc.AddSubOperator(seqProc);
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339 | modelAnalyser.OperatorGraph.InitialOperator = seqSubScopeProc;
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340 | modelAnalyser.OperatorGraph.AddOperator(seqSubScopeProc);
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341 | return modelAnalyser;
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342 | }
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343 |
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344 |
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345 | protected internal virtual Model CreateSVMModel(IScope bestModelScope) {
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346 | Model model = new Model();
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347 | model.TrainingMeanSquaredError = bestModelScope.GetVariableValue<DoubleData>("Quality", false).Data;
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348 | model.ValidationMeanSquaredError = bestModelScope.GetVariableValue<DoubleData>("ValidationQuality", false).Data;
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349 | model.TestMeanSquaredError = bestModelScope.GetVariableValue<DoubleData>("TestQuality", false).Data;
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350 | model.TrainingCoefficientOfDetermination = bestModelScope.GetVariableValue<DoubleData>("TrainingR2", false).Data;
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351 | model.ValidationCoefficientOfDetermination = bestModelScope.GetVariableValue<DoubleData>("ValidationR2", false).Data;
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352 | model.TestCoefficientOfDetermination = bestModelScope.GetVariableValue<DoubleData>("TestR2", false).Data;
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353 | model.TrainingMeanAbsolutePercentageError = bestModelScope.GetVariableValue<DoubleData>("TrainingMAPE", false).Data;
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354 | model.ValidationMeanAbsolutePercentageError = bestModelScope.GetVariableValue<DoubleData>("ValidationMAPE", false).Data;
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355 | model.TestMeanAbsolutePercentageError = bestModelScope.GetVariableValue<DoubleData>("TestMAPE", false).Data;
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356 | model.TrainingMeanAbsolutePercentageOfRangeError = bestModelScope.GetVariableValue<DoubleData>("TrainingMAPRE", false).Data;
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357 | model.ValidationMeanAbsolutePercentageOfRangeError = bestModelScope.GetVariableValue<DoubleData>("ValidationMAPRE", false).Data;
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358 | model.TestMeanAbsolutePercentageOfRangeError = bestModelScope.GetVariableValue<DoubleData>("TestMAPRE", false).Data;
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359 | model.TrainingVarianceAccountedFor = bestModelScope.GetVariableValue<DoubleData>("TrainingVAF", false).Data;
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360 | model.ValidationVarianceAccountedFor = bestModelScope.GetVariableValue<DoubleData>("ValidationVAF", false).Data;
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361 | model.TestVarianceAccountedFor = bestModelScope.GetVariableValue<DoubleData>("TestVAF", false).Data;
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362 |
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363 | model.Data = bestModelScope.GetVariableValue<SVMModel>("Model", false);
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364 | HeuristicLab.DataAnalysis.Dataset ds = bestModelScope.GetVariableValue<Dataset>("Dataset", true);
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365 | model.Dataset = ds;
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366 | model.TargetVariable = ds.GetVariableName(bestModelScope.GetVariableValue<IntData>("TargetVariable", true).Data);
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367 |
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368 | ItemList evaluationImpacts = bestModelScope.GetVariableValue<ItemList>("VariableEvaluationImpacts", false);
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369 | ItemList qualityImpacts = bestModelScope.GetVariableValue<ItemList>("VariableQualityImpacts", false);
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370 | foreach (ItemList row in evaluationImpacts) {
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371 | string variableName = ((StringData)row[0]).Data;
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372 | double impact = ((DoubleData)row[1]).Data;
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373 | model.SetVariableEvaluationImpact(variableName, impact);
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374 | }
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375 | foreach (ItemList row in qualityImpacts) {
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376 | string variableName = ((StringData)row[0]).Data;
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377 | double impact = ((DoubleData)row[1]).Data;
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378 | model.SetVariableQualityImpact(variableName, impact);
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379 | }
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380 |
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381 | return model;
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382 | }
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383 |
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384 | private IOperator GetVariableInjector() {
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385 | return GetMainOperator().SubOperators[0];
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386 | }
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387 |
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388 | private IOperator GetMainOperator() {
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389 | CombinedOperator svm = (CombinedOperator)Engine.OperatorGraph.InitialOperator;
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390 | return svm.OperatorGraph.InitialOperator;
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391 | }
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392 |
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393 | public override IView CreateView() {
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394 | return engine.CreateView();
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395 | }
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396 |
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397 | #region IEditable Members
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398 |
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399 | public IEditor CreateEditor() {
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400 | return engine.CreateEditor();
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401 | }
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402 |
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403 | #endregion
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404 | }
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405 | }
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