1 | using System;
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2 | using System.Collections.Generic;
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3 | using System.Linq;
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4 | using System.Text;
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5 | using HeuristicLab.GP;
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6 | using HeuristicLab.Core;
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7 | using HeuristicLab.GP.StructureIdentification;
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8 | using System.IO;
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9 | using HeuristicLab.Data;
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10 | using SVM;
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11 | using HeuristicLab.DataAnalysis;
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12 | using HeuristicLab.Modeling.Database;
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13 |
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14 | namespace CedmaExporter {
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15 | class CedmaExporter {
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16 |
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17 | public static List<string> WriteVariableImpactHeaders(HeuristicLab.Modeling.Database.SQLServerCompact.DatabaseService database, StreamWriter writer) {
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18 | List<string> inputVarNames = new List<string>();
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19 | var variables = database.GetAllVariables();
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20 | foreach (var r in database.GetAllResultsForInputVariables()) {
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21 | foreach (string varName in variables.Keys) {
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22 | writer.Write(r.Name); writer.Write(": "); writer.Write(varName); writer.Write("; ");
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23 | }
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24 | }
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25 | writer.WriteLine();
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26 | return new List<string>(variables.Keys);
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27 | }
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28 |
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29 | public static void WriteModel(IModel model, int id, HeuristicLab.Modeling.Database.IModelingDatabase database, StreamWriter writer, List<string> inputVariables, ModelExporter exporter) {
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30 | try {
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31 | writer.Write(id); writer.Write("; ");
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32 | string targetVariable = model.TargetVariable.Name;
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33 | string algoName = model.Algorithm.Name;
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34 | string modelFileName = "model_" + targetVariable + "_" + id.ToString("000");
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35 | writer.Write(modelFileName); writer.Write("; ");
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36 | writer.Write(targetVariable); writer.Write("; ");
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37 | writer.Write(algoName); writer.Write("; ");
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38 | var modelResults = database.GetModelResults(model);
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39 | writer.Write(FindResult("TrainingMeanSquaredError", modelResults)); writer.Write("; ");
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40 | writer.Write(FindResult("ValidationMeanSquaredError", modelResults)); writer.Write("; ");
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41 | writer.Write(FindResult("TestMeanSquaredError", modelResults)); writer.Write("; ");
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42 | writer.Write(FindResult("TrainingCoefficientOfDetermination", modelResults)); writer.Write("; ");
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43 | writer.Write(FindResult("ValidationCoefficientOfDetermination", modelResults)); writer.Write("; ");
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44 | writer.Write(FindResult("TestCoefficientOfDetermination", modelResults)); writer.Write("; ");
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45 | writer.Write(FindResult("TrainingMeanAbsolutePercentageError", modelResults)); writer.Write("; ");
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46 | writer.Write(FindResult("ValidationMeanAbsolutePercentageError", modelResults)); writer.Write("; ");
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47 | writer.Write(FindResult("TestMeanAbsolutePercentageError", modelResults)); writer.Write("; ");
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48 | writer.Write(FindResult("TrainingMeanAbsolutePercentageOfRangeError", modelResults)); writer.Write("; ");
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49 | writer.Write(FindResult("ValidationMeanAbsolutePercentageOfRangeError", modelResults)); writer.Write("; ");
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50 | writer.Write(FindResult("TestMeanAbsolutePercentageOfRangeError", modelResults)); writer.Write("; ");
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51 | writer.Write(FindResult("TrainingVarianceAccountedFor", modelResults)); writer.Write("; ");
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52 | writer.Write(FindResult("ValidationVarianceAccountedFor", modelResults)); writer.Write("; ");
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53 | writer.Write(FindResult("TestVarianceAccountedFor", modelResults)); writer.Write("; ");
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54 | WriteVariableImpacts(writer, database, model, inputVariables);
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55 | // exporter.Export(modelFileName, data);
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56 | }
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57 | catch (FormatException ex) {
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58 | // ignore
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59 | }
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60 | finally {
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61 | writer.WriteLine();
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62 | }
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63 | }
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64 |
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65 | private static void WriteVariableImpacts(StreamWriter writer, IModelingDatabase database, IModel model, List<string> inputVariables) {
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66 | Dictionary<string, List<IInputVariableResult>> impacts = new Dictionary<string, List<IInputVariableResult>>();
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67 | foreach (var inputVariableResult in database.GetInputVariableResults(model)) {
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68 | if (!impacts.ContainsKey(inputVariableResult.Variable.Name))
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69 | impacts[inputVariableResult.Variable.Name] = new List<IInputVariableResult>();
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70 | impacts[inputVariableResult.Variable.Name].Add(inputVariableResult);
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71 | }
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72 |
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73 | foreach (string varName in inputVariables) {
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74 | if (impacts.ContainsKey(varName)) {
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75 | writer.Write(FindResult("VariableEvaluationImpact", impacts[varName])); writer.Write("; ");
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76 | } else {
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77 | writer.Write(" ; ");
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78 | }
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79 | }
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80 |
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81 | foreach (string varName in inputVariables) {
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82 | if (impacts.ContainsKey(varName)) {
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83 | writer.Write(FindResult("VariableQualityImpact", impacts[varName])); writer.Write("; ");
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84 | } else {
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85 | writer.Write(" ; ");
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86 | }
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87 | }
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88 | }
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89 |
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90 | private static double FindResult(string p, List<IInputVariableResult> rs) {
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91 | return rs.First(e => e.Result.Name == p).Value;
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92 | }
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93 |
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94 | private static double FindResult(string p, IEnumerable<IModelResult> rs) {
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95 | return rs.First(e => e.Result.Name == p).Value;
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96 | }
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97 |
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98 | public static void WriteColumnHeaders(StreamWriter writer) {
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99 | writer.Write("Id; Filename; TargetVariable; Algorithm;" +
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100 | "TrainingMSE; ValidationMSE; TestMSE; " +
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101 | "TrainingR2; ValidationR2; TestR2; " +
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102 | "TrainingMAPE; ValidationMAPE; TestMAPE; " +
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103 | "TrainingMAPRE; ValidationMAPRE; TestMAPRE; " +
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104 | "TrainingVAF; ValidationVAF; TestVAF; ");
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105 | }
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106 | }
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107 | class ModelExporter {
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108 | private string outputDir;
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109 | private bool debugging;
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110 | private Dataset dataset;
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111 |
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112 | public ModelExporter(Dataset ds, string outputDir, bool debugging) {
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113 | this.dataset = ds;
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114 | this.outputDir = outputDir;
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115 | this.debugging = debugging;
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116 | }
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117 |
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118 | public void Export(string modelFileName, IStorable model) {
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119 | //if (debugging) return;
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120 | //foreach (char c in Path.GetInvalidFileNameChars()) {
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121 | // modelFileName = modelFileName.Replace(c, '_');
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122 | //}
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123 | //if (model is Predictor) {
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124 | // using (StreamWriter writer = File.CreateText(Path.Combine(outputDir, modelFileName + ".gp.txt"))) {
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125 | // writer.Write(treeExporter.Export(((Predictor)model).FunctionTree);
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126 | // }
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127 | //} else if (model is HeuristicLab.SupportVectorMachines.Predictor) {
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128 | // SVMModel svmModel = (SVMModel)model;
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129 | // RangeTransform.Write(Path.Combine(outputDir, modelFileName + ".svm.transform.txt"), svmModel.RangeTransform);
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130 | // SVM.Model.Write(Path.Combine(outputDir, modelFileName + ".svm.model.txt"), svmModel.Model);
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131 | //} else throw new NotSupportedException("This type of model is not supported by the CedmaExporter: " + model);
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132 | }
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133 | }
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134 | }
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