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.Logging;
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33 | using HeuristicLab.Operators.Programmable;
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34 | using HeuristicLab.Modeling;
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35 | using HeuristicLab.Random;
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36 | using HeuristicLab.Selection;
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37 |
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38 | namespace HeuristicLab.SupportVectorMachines {
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39 | public class SupportVectorRegression : ItemBase, IEditable, IAlgorithm {
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40 |
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41 | public string Name { get { return "SupportVectorRegression"; } }
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42 | public string Description { get { return "TODO"; } }
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43 |
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44 | private SequentialEngine.SequentialEngine engine;
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45 | public IEngine Engine {
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46 | get { return engine; }
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47 | }
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48 |
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49 | public Dataset Dataset {
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50 | get { return ProblemInjector.GetVariableValue<Dataset>("Dataset", null, false); }
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51 | set { ProblemInjector.GetVariable("Dataset").Value = value; }
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52 | }
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53 |
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54 | public int TargetVariable {
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55 | get { return ProblemInjector.GetVariableValue<IntData>("TargetVariable", null, false).Data; }
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56 | set { ProblemInjector.GetVariableValue<IntData>("TargetVariable", null, false).Data = value; }
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57 | }
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58 |
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59 | public IOperator ProblemInjector {
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60 | get {
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61 | IOperator main = GetMainOperator();
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62 | return main.SubOperators[0].SubOperators[1];
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63 | }
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64 | set {
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65 | IOperator main = GetMainOperator();
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66 | main.RemoveSubOperator(1);
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67 | main.AddSubOperator(value, 1);
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68 | }
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69 | }
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70 |
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71 | public IAnalyzerModel Model {
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72 | get {
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73 | 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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74 | IScope bestModelScope = engine.GlobalScope.SubScopes[0];
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75 | return CreateSVMModel(bestModelScope);
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76 | }
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77 | }
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78 |
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79 | public DoubleArrayData NuList {
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80 | get { return GetVariableInjector().GetVariable("NuList").GetValue<DoubleArrayData>(); }
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81 | set { GetVariableInjector().GetVariable("NuList").Value = value; }
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82 | }
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83 |
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84 | public int MaxNuIndex {
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85 | get { return GetVariableInjector().GetVariable("MaxNuIndex").GetValue<IntData>().Data; }
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86 | set { GetVariableInjector().GetVariable("MaxNuIndex").GetValue<IntData>().Data = value; }
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87 | }
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88 |
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89 | public DoubleArrayData CostList {
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90 | get { return GetVariableInjector().GetVariable("CostList").GetValue<DoubleArrayData>(); }
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91 | set { GetVariableInjector().GetVariable("CostList").Value = value; }
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92 | }
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93 |
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94 | public int MaxCostIndex {
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95 | get { return GetVariableInjector().GetVariable("MaxCostIndex").GetValue<IntData>().Data; }
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96 | set { GetVariableInjector().GetVariable("MaxCostIndex").GetValue<IntData>().Data = value; }
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97 | }
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98 |
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99 | public DoubleArrayData GammaList {
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100 | get { return GetVariableInjector().GetVariable("GammaList").GetValue<DoubleArrayData>(); }
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101 | set { GetVariableInjector().GetVariable("GammaList").Value = value; }
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102 | }
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103 |
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104 | public int MaxGammaIndex {
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105 | get { return GetVariableInjector().GetVariable("MaxGammaIndex").GetValue<IntData>().Data; }
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106 | set { GetVariableInjector().GetVariable("MaxGammaIndex").GetValue<IntData>().Data = value; }
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107 | }
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108 |
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109 | public SupportVectorRegression() {
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110 | engine = new SequentialEngine.SequentialEngine();
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111 | CombinedOperator algo = CreateAlgorithm();
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112 | engine.OperatorGraph.AddOperator(algo);
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113 | engine.OperatorGraph.InitialOperator = algo;
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114 | MaxCostIndex = CostList.Data.Length;
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115 | MaxNuIndex = NuList.Data.Length;
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116 | MaxGammaIndex = GammaList.Data.Length;
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117 | }
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118 |
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119 | private CombinedOperator CreateAlgorithm() {
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120 | CombinedOperator algo = new CombinedOperator();
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121 | SequentialProcessor seq = new SequentialProcessor();
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122 | algo.Name = "SupportVectorRegression";
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123 | seq.Name = "SupportVectorRegression";
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124 |
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125 | IOperator initialization = CreateInitialization();
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126 | IOperator main = CreateMainLoop();
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127 | IOperator postProc = CreateModelAnalyser();
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128 |
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129 | seq.AddSubOperator(initialization);
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130 | seq.AddSubOperator(main);
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131 | seq.AddSubOperator(postProc);
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132 |
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133 | algo.OperatorGraph.InitialOperator = seq;
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134 | algo.OperatorGraph.AddOperator(seq);
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135 |
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136 | return algo;
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137 | }
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138 |
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139 | private IOperator CreateInitialization() {
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140 | SequentialProcessor seq = new SequentialProcessor();
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141 | seq.Name = "Initialization";
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142 | seq.AddSubOperator(CreateGlobalInjector());
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143 | ProblemInjector probInjector = new ProblemInjector();
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144 | probInjector.GetVariableInfo("MaxNumberOfTrainingSamples").Local = true;
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145 | probInjector.AddVariable(new Variable("MaxNumberOfTrainingSamples", new IntData(1000)));
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146 | seq.AddSubOperator(probInjector);
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147 | seq.AddSubOperator(new RandomInjector());
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148 |
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149 | DatasetShuffler shuffler = new DatasetShuffler();
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150 | shuffler.GetVariableInfo("ShuffleStart").ActualName = "TrainingSamplesStart";
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151 | shuffler.GetVariableInfo("ShuffleEnd").ActualName = "TrainingSamplesEnd";
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152 | seq.AddSubOperator(shuffler);
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153 | return seq;
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154 | }
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155 |
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156 | private IOperator CreateMainLoop() {
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157 | SequentialProcessor main = new SequentialProcessor();
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158 | main.Name = "Main";
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159 | #region initial solution
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160 | SubScopesCreater modelScopeCreator = new SubScopesCreater();
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161 | modelScopeCreator.GetVariableInfo("SubScopes").Local = true;
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162 | modelScopeCreator.AddVariable(new HeuristicLab.Core.Variable("SubScopes", new IntData(1)));
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163 | main.AddSubOperator(modelScopeCreator);
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164 |
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165 | SequentialSubScopesProcessor seqSubScopesProc = new SequentialSubScopesProcessor();
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166 | IOperator modelProcessor = CreateModelProcessor();
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167 |
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168 | seqSubScopesProc.AddSubOperator(modelProcessor);
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169 | main.AddSubOperator(seqSubScopesProc);
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170 | #endregion
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171 |
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172 | SequentialProcessor nuLoop = new SequentialProcessor();
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173 | nuLoop.Name = "NuLoop";
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174 |
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175 | SequentialProcessor gammaLoop = new SequentialProcessor();
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176 | gammaLoop.Name = "GammaLoop";
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177 |
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178 | nuLoop.AddSubOperator(gammaLoop);
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179 |
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180 | IOperator costCounter = CreateCounter("Cost");
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181 | IOperator costComparator = CreateComparator("Cost");
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182 | gammaLoop.AddSubOperator(costCounter);
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183 | gammaLoop.AddSubOperator(costComparator);
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184 |
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185 | ConditionalBranch costBranch = new ConditionalBranch();
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186 | costBranch.Name = "IfValidCostIndex";
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187 | costBranch.GetVariableInfo("Condition").ActualName = "RepeatCostLoop";
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188 |
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189 | // build cost loop
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190 | SequentialProcessor costLoop = new SequentialProcessor();
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191 | costLoop.Name = "CostLoop";
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192 |
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193 | #region selection of better solution
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194 | costLoop.AddSubOperator(modelScopeCreator);
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195 | SequentialSubScopesProcessor subScopesProcessor = new SequentialSubScopesProcessor();
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196 | costLoop.AddSubOperator(subScopesProcessor);
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197 | subScopesProcessor.AddSubOperator(new EmptyOperator());
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198 | subScopesProcessor.AddSubOperator(modelProcessor);
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199 |
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200 | Sorter sorter = new Sorter();
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201 | sorter.GetVariableInfo("Value").ActualName = "ValidationQuality";
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202 | sorter.GetVariableInfo("Descending").Local = true;
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203 | sorter.AddVariable(new Variable("Descending", new BoolData(false)));
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204 | costLoop.AddSubOperator(sorter);
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205 |
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206 | LeftSelector selector = new LeftSelector();
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207 | selector.GetVariableInfo("Selected").Local = true;
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208 | selector.AddVariable(new Variable("Selected", new IntData(1)));
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209 | costLoop.AddSubOperator(selector);
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210 |
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211 | RightReducer reducer = new RightReducer();
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212 | costLoop.AddSubOperator(reducer);
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213 | #endregion
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214 |
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215 | costLoop.AddSubOperator(costCounter);
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216 | costLoop.AddSubOperator(costComparator);
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217 |
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218 | costBranch.AddSubOperator(costLoop);
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219 | costLoop.AddSubOperator(costBranch);
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220 |
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221 | gammaLoop.AddSubOperator(costBranch); // inner loop
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222 | gammaLoop.AddSubOperator(CreateResetOperator("CostIndex", -1));
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223 | gammaLoop.AddSubOperator(CreateCounter("Gamma"));
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224 | gammaLoop.AddSubOperator(CreateComparator("Gamma"));
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225 |
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226 | ConditionalBranch gammaBranch = new ConditionalBranch();
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227 | gammaBranch.Name = "GammaLoop";
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228 | gammaBranch.GetVariableInfo("Condition").ActualName = "RepeatGammaLoop";
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229 | gammaBranch.AddSubOperator(gammaLoop);
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230 | gammaLoop.AddSubOperator(gammaBranch);
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231 |
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232 | nuLoop.AddSubOperator(CreateResetOperator("GammaIndex", 0));
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233 |
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234 | nuLoop.AddSubOperator(CreateCounter("Nu"));
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235 | nuLoop.AddSubOperator(CreateComparator("Nu"));
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236 |
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237 | ConditionalBranch nuBranch = new ConditionalBranch();
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238 | nuBranch.Name = "NuLoop";
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239 | nuBranch.GetVariableInfo("Condition").ActualName = "RepeatNuLoop";
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240 |
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241 | nuBranch.AddSubOperator(nuLoop);
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242 | nuLoop.AddSubOperator(nuBranch);
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243 |
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244 | main.AddSubOperator(nuLoop);
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245 | return main;
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246 | }
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247 |
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248 | private IOperator CreateModelProcessor() {
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249 | SequentialProcessor modelProcessor = new SequentialProcessor();
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250 | modelProcessor.AddSubOperator(CreateSetNextParameterValueOperator("Nu"));
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251 | modelProcessor.AddSubOperator(CreateSetNextParameterValueOperator("Cost"));
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252 | modelProcessor.AddSubOperator(CreateSetNextParameterValueOperator("Gamma"));
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253 |
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254 | SupportVectorCreator modelCreator = new SupportVectorCreator();
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255 | modelCreator.GetVariableInfo("SamplesStart").ActualName = "ActualTrainingSamplesStart";
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256 | modelCreator.GetVariableInfo("SamplesEnd").ActualName = "ActualTrainingSamplesEnd";
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257 | modelCreator.GetVariableInfo("SVMCost").ActualName = "Cost";
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258 | modelCreator.GetVariableInfo("SVMGamma").ActualName = "Gamma";
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259 | modelCreator.GetVariableInfo("SVMKernelType").ActualName = "KernelType";
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260 | modelCreator.GetVariableInfo("SVMModel").ActualName = "Model";
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261 | modelCreator.GetVariableInfo("SVMNu").ActualName = "Nu";
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262 | modelCreator.GetVariableInfo("SVMType").ActualName = "Type";
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263 |
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264 | modelProcessor.AddSubOperator(modelCreator);
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265 | CombinedOperator trainingEvaluator = (CombinedOperator)CreateEvaluator("ActualTraining");
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266 | trainingEvaluator.OperatorGraph.InitialOperator.SubOperators[1].GetVariableInfo("MSE").ActualName = "Quality";
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267 | modelProcessor.AddSubOperator(trainingEvaluator);
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268 | modelProcessor.AddSubOperator(CreateEvaluator("Validation"));
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269 | modelProcessor.AddSubOperator(CreateEvaluator("Test"));
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270 |
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271 | DataCollector collector = new DataCollector();
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272 | collector.GetVariableInfo("Values").ActualName = "Log";
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273 | ((ItemList<StringData>)collector.GetVariable("VariableNames").Value).Add(new StringData("Nu"));
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274 | ((ItemList<StringData>)collector.GetVariable("VariableNames").Value).Add(new StringData("Cost"));
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275 | ((ItemList<StringData>)collector.GetVariable("VariableNames").Value).Add(new StringData("Gamma"));
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276 | ((ItemList<StringData>)collector.GetVariable("VariableNames").Value).Add(new StringData("ValidationQuality"));
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277 | modelProcessor.AddSubOperator(collector);
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278 | return modelProcessor;
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279 | }
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280 |
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281 | private IOperator CreateComparator(string p) {
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282 | LessThanComparator comparator = new LessThanComparator();
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283 | comparator.Name = p + "IndexComparator";
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284 | comparator.GetVariableInfo("LeftSide").ActualName = p + "Index";
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285 | comparator.GetVariableInfo("RightSide").ActualName = "Max" + p + "Index";
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286 | comparator.GetVariableInfo("Result").ActualName = "Repeat" + p + "Loop";
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287 | return comparator;
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288 | }
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289 |
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290 | private IOperator CreateCounter(string p) {
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291 | Counter c = new Counter();
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292 | c.GetVariableInfo("Value").ActualName = p + "Index";
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293 | c.Name = p + "Counter";
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294 | return c;
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295 | }
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296 |
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297 | private IOperator CreateEvaluator(string p) {
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298 | CombinedOperator op = new CombinedOperator();
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299 | op.Name = p + "Evaluator";
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300 | SequentialProcessor seqProc = new SequentialProcessor();
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301 |
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302 | SupportVectorEvaluator evaluator = new SupportVectorEvaluator();
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303 | evaluator.Name = p + "SimpleEvaluator";
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304 | evaluator.GetVariableInfo("SVMModel").ActualName = "Model";
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305 | evaluator.GetVariableInfo("SamplesStart").ActualName = p + "SamplesStart";
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306 | evaluator.GetVariableInfo("SamplesEnd").ActualName = p + "SamplesEnd";
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307 | evaluator.GetVariableInfo("Values").ActualName = p + "Values";
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308 | SimpleMSEEvaluator mseEvaluator = new SimpleMSEEvaluator();
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309 | mseEvaluator.Name = p + "MseEvaluator";
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310 | mseEvaluator.GetVariableInfo("Values").ActualName = p + "Values";
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311 | mseEvaluator.GetVariableInfo("MSE").ActualName = p + "Quality";
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312 | SimpleR2Evaluator r2Evaluator = new SimpleR2Evaluator();
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313 | r2Evaluator.Name = p + "R2Evaluator";
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314 | r2Evaluator.GetVariableInfo("Values").ActualName = p + "Values";
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315 | r2Evaluator.GetVariableInfo("R2").ActualName = p + "R2";
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316 | SimpleMeanAbsolutePercentageErrorEvaluator mapeEvaluator = new SimpleMeanAbsolutePercentageErrorEvaluator();
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317 | mapeEvaluator.Name = p + "MAPEEvaluator";
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318 | mapeEvaluator.GetVariableInfo("Values").ActualName = p + "Values";
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319 | mapeEvaluator.GetVariableInfo("MAPE").ActualName = p + "MAPE";
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320 | SimpleMeanAbsolutePercentageOfRangeErrorEvaluator mapreEvaluator = new SimpleMeanAbsolutePercentageOfRangeErrorEvaluator();
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321 | mapreEvaluator.Name = p + "MAPREEvaluator";
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322 | mapreEvaluator.GetVariableInfo("Values").ActualName = p + "Values";
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323 | mapreEvaluator.GetVariableInfo("MAPRE").ActualName = p + "MAPRE";
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324 | SimpleVarianceAccountedForEvaluator vafEvaluator = new SimpleVarianceAccountedForEvaluator();
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325 | vafEvaluator.Name = p + "VAFEvaluator";
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326 | vafEvaluator.GetVariableInfo("Values").ActualName = p + "Values";
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327 | vafEvaluator.GetVariableInfo("VAF").ActualName = p + "VAF";
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328 |
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329 | seqProc.AddSubOperator(evaluator);
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330 | seqProc.AddSubOperator(mseEvaluator);
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331 | seqProc.AddSubOperator(r2Evaluator);
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332 | seqProc.AddSubOperator(mapeEvaluator);
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333 | seqProc.AddSubOperator(mapreEvaluator);
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334 | seqProc.AddSubOperator(vafEvaluator);
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335 |
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336 | op.OperatorGraph.AddOperator(seqProc);
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337 | op.OperatorGraph.InitialOperator = seqProc;
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338 | return op;
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339 | }
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340 |
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341 | private IOperator CreateSetNextParameterValueOperator(string paramName) {
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342 | ProgrammableOperator progOp = new ProgrammableOperator();
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343 | progOp.Name = "SetNext" + paramName;
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344 | progOp.RemoveVariableInfo("Result");
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345 | progOp.AddVariableInfo(new VariableInfo("Value", "Value", typeof(DoubleData), VariableKind.New));
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346 | progOp.AddVariableInfo(new VariableInfo("ValueIndex", "ValueIndex", typeof(IntData), VariableKind.In));
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347 | progOp.AddVariableInfo(new VariableInfo("ValueList", "ValueList", typeof(DoubleArrayData), VariableKind.In));
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348 | progOp.Code =
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349 | @"
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350 | Value.Data = ValueList.Data[ValueIndex.Data];
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351 | ";
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352 |
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353 | progOp.GetVariableInfo("Value").ActualName = paramName;
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354 | progOp.GetVariableInfo("ValueIndex").ActualName = paramName + "Index";
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355 | progOp.GetVariableInfo("ValueList").ActualName = paramName + "List";
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356 | return progOp;
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357 | }
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358 |
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359 | private IOperator CreateResetOperator(string paramName, int value) {
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360 | ProgrammableOperator progOp = new ProgrammableOperator();
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361 | progOp.Name = "Reset" + paramName;
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362 | progOp.RemoveVariableInfo("Result");
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363 | progOp.AddVariableInfo(new VariableInfo("Value", "Value", typeof(IntData), VariableKind.In | VariableKind.Out));
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364 | progOp.Code = "Value.Data = " + value + ";";
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365 | progOp.GetVariableInfo("Value").ActualName = paramName;
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366 | return progOp;
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367 | }
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368 |
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369 | private IOperator CreateGlobalInjector() {
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370 | VariableInjector injector = new VariableInjector();
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371 | injector.AddVariable(new HeuristicLab.Core.Variable("CostIndex", new IntData(0)));
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372 | injector.AddVariable(new HeuristicLab.Core.Variable("CostList", new DoubleArrayData(new double[] {
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373 | Math.Pow(2,-5),
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374 | Math.Pow(2,-3),
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375 | Math.Pow(2,-1),
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376 | 2,
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377 | Math.Pow(2,3),
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378 | Math.Pow(2,5),
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379 | Math.Pow(2,7),
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380 | Math.Pow(2,9),
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381 | Math.Pow(2,11),
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382 | Math.Pow(2,13),
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383 | Math.Pow(2,15)})));
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384 | injector.AddVariable(new HeuristicLab.Core.Variable("MaxCostIndex", new IntData()));
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385 | injector.AddVariable(new HeuristicLab.Core.Variable("NuIndex", new IntData(0)));
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386 | injector.AddVariable(new HeuristicLab.Core.Variable("NuList", new DoubleArrayData(new double[] { 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.9, 0.8, 1 })));
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387 | injector.AddVariable(new HeuristicLab.Core.Variable("MaxNuIndex", new IntData()));
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388 | injector.AddVariable(new HeuristicLab.Core.Variable("Log", new ItemList()));
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389 | injector.AddVariable(new HeuristicLab.Core.Variable("GammaIndex", new IntData(0)));
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390 | injector.AddVariable(new HeuristicLab.Core.Variable("GammaList", new DoubleArrayData(new double[] {
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391 | 3.0517578125E-05, 0.0001220703125,0.00048828125,0.001953125,
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392 | 0.0078125,0.03125,0.125,0.5,2,4,8})));
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393 | injector.AddVariable(new HeuristicLab.Core.Variable("MaxGammaIndex", new IntData()));
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394 | injector.AddVariable(new HeuristicLab.Core.Variable("KernelType", new StringData("RBF")));
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395 | injector.AddVariable(new HeuristicLab.Core.Variable("Type", new StringData("NU_SVR")));
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396 |
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397 | return injector;
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398 | }
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399 |
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400 | private IOperator CreateModelAnalyser() {
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401 | CombinedOperator modelAnalyser = new CombinedOperator();
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402 | modelAnalyser.Name = "Model Analyzer";
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403 | SequentialSubScopesProcessor seqSubScopeProc = new SequentialSubScopesProcessor();
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404 | SequentialProcessor seqProc = new SequentialProcessor();
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405 | VariableEvaluationImpactCalculator evalImpactCalc = new VariableEvaluationImpactCalculator();
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406 | evalImpactCalc.GetVariableInfo("TrainingSamplesStart").ActualName = "ActualTrainingSamplesStart";
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407 | evalImpactCalc.GetVariableInfo("TrainingSamplesEnd").ActualName = "ActualTrainingSamplesEnd";
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408 | evalImpactCalc.GetVariableInfo("SVMModel").ActualName = "Model";
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409 | VariableQualityImpactCalculator qualImpactCalc = new VariableQualityImpactCalculator();
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410 | qualImpactCalc.GetVariableInfo("TrainingSamplesStart").ActualName = "ActualTrainingSamplesStart";
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411 | qualImpactCalc.GetVariableInfo("TrainingSamplesEnd").ActualName = "ActualTrainingSamplesEnd";
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412 | qualImpactCalc.GetVariableInfo("SVMModel").ActualName = "Model";
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413 |
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414 | seqProc.AddSubOperator(evalImpactCalc);
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415 | seqProc.AddSubOperator(qualImpactCalc);
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416 | seqSubScopeProc.AddSubOperator(seqProc);
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417 | modelAnalyser.OperatorGraph.InitialOperator = seqSubScopeProc;
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418 | modelAnalyser.OperatorGraph.AddOperator(seqSubScopeProc);
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419 | return modelAnalyser;
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420 | }
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421 |
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422 |
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423 | protected internal virtual IAnalyzerModel CreateSVMModel(IScope bestModelScope) {
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424 | AnalyzerModel model = new AnalyzerModel();
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425 | model.TrainingMeanSquaredError = bestModelScope.GetVariableValue<DoubleData>("Quality", false).Data;
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426 | model.ValidationMeanSquaredError = bestModelScope.GetVariableValue<DoubleData>("ValidationQuality", false).Data;
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427 | model.TestMeanSquaredError = bestModelScope.GetVariableValue<DoubleData>("TestQuality", false).Data;
|
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428 | model.TrainingCoefficientOfDetermination = bestModelScope.GetVariableValue<DoubleData>("ActualTrainingR2", false).Data;
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429 | model.ValidationCoefficientOfDetermination = bestModelScope.GetVariableValue<DoubleData>("ValidationR2", false).Data;
|
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430 | model.TestCoefficientOfDetermination = bestModelScope.GetVariableValue<DoubleData>("TestR2", false).Data;
|
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431 | model.TrainingMeanAbsolutePercentageError = bestModelScope.GetVariableValue<DoubleData>("ActualTrainingMAPE", false).Data;
|
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432 | model.ValidationMeanAbsolutePercentageError = bestModelScope.GetVariableValue<DoubleData>("ValidationMAPE", false).Data;
|
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433 | model.TestMeanAbsolutePercentageError = bestModelScope.GetVariableValue<DoubleData>("TestMAPE", false).Data;
|
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434 | model.TrainingMeanAbsolutePercentageOfRangeError = bestModelScope.GetVariableValue<DoubleData>("ActualTrainingMAPRE", false).Data;
|
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435 | model.ValidationMeanAbsolutePercentageOfRangeError = bestModelScope.GetVariableValue<DoubleData>("ValidationMAPRE", false).Data;
|
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436 | model.TestMeanAbsolutePercentageOfRangeError = bestModelScope.GetVariableValue<DoubleData>("TestMAPRE", false).Data;
|
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437 | model.TrainingVarianceAccountedFor = bestModelScope.GetVariableValue<DoubleData>("ActualTrainingVAF", false).Data;
|
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438 | model.ValidationVarianceAccountedFor = bestModelScope.GetVariableValue<DoubleData>("ValidationVAF", false).Data;
|
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439 | model.TestVarianceAccountedFor = bestModelScope.GetVariableValue<DoubleData>("TestVAF", false).Data;
|
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440 |
|
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441 | HeuristicLab.DataAnalysis.Dataset ds = bestModelScope.GetVariableValue<Dataset>("Dataset", true);
|
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442 | model.Dataset = ds;
|
---|
443 | model.TargetVariable = ds.GetVariableName(bestModelScope.GetVariableValue<IntData>("TargetVariable", true).Data);
|
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444 | model.TrainingSamplesStart = bestModelScope.GetVariableValue<IntData>("TrainingSamplesStart", true).Data;
|
---|
445 | model.TrainingSamplesEnd = bestModelScope.GetVariableValue<IntData>("TrainingSamplesEnd", true).Data;
|
---|
446 | model.ValidationSamplesStart = bestModelScope.GetVariableValue<IntData>("ValidationSamplesStart", true).Data;
|
---|
447 | model.ValidationSamplesEnd = bestModelScope.GetVariableValue<IntData>("ValidationSamplesEnd", true).Data;
|
---|
448 | model.TestSamplesStart = bestModelScope.GetVariableValue<IntData>("TestSamplesStart", true).Data;
|
---|
449 | model.TestSamplesEnd = bestModelScope.GetVariableValue<IntData>("TestSamplesEnd", true).Data;
|
---|
450 | Dictionary<string, int> variableNames = new Dictionary<string, int>();
|
---|
451 | for (int i = 0; i < ds.Columns; i++) variableNames[ds.GetVariableName(i)] = i;
|
---|
452 | model.Predictor = new Predictor(bestModelScope.GetVariableValue<SVMModel>("Model", false), model.TargetVariable, variableNames);
|
---|
453 |
|
---|
454 |
|
---|
455 | ItemList evaluationImpacts = bestModelScope.GetVariableValue<ItemList>("VariableEvaluationImpacts", false);
|
---|
456 | ItemList qualityImpacts = bestModelScope.GetVariableValue<ItemList>("VariableQualityImpacts", false);
|
---|
457 | foreach (ItemList row in evaluationImpacts) {
|
---|
458 | string variableName = ((StringData)row[0]).Data;
|
---|
459 | double impact = ((DoubleData)row[1]).Data;
|
---|
460 | model.SetVariableEvaluationImpact(variableName, impact);
|
---|
461 | model.AddInputVariable(variableName);
|
---|
462 | }
|
---|
463 | foreach (ItemList row in qualityImpacts) {
|
---|
464 | string variableName = ((StringData)row[0]).Data;
|
---|
465 | double impact = ((DoubleData)row[1]).Data;
|
---|
466 | model.SetVariableQualityImpact(variableName, impact);
|
---|
467 | model.AddInputVariable(variableName);
|
---|
468 | }
|
---|
469 |
|
---|
470 | return model;
|
---|
471 | }
|
---|
472 |
|
---|
473 | private IOperator GetVariableInjector() {
|
---|
474 | return GetMainOperator().SubOperators[0].SubOperators[0];
|
---|
475 | }
|
---|
476 |
|
---|
477 | private IOperator GetMainOperator() {
|
---|
478 | CombinedOperator svm = (CombinedOperator)Engine.OperatorGraph.InitialOperator;
|
---|
479 | return svm.OperatorGraph.InitialOperator;
|
---|
480 | }
|
---|
481 |
|
---|
482 | public override IView CreateView() {
|
---|
483 | return engine.CreateView();
|
---|
484 | }
|
---|
485 |
|
---|
486 | #region IEditable Members
|
---|
487 |
|
---|
488 | public IEditor CreateEditor() {
|
---|
489 | return engine.CreateEditor();
|
---|
490 | }
|
---|
491 |
|
---|
492 | #endregion
|
---|
493 | }
|
---|
494 | }
|
---|