- Timestamp:
- 09/08/09 11:11:50 (15 years ago)
- Location:
- trunk/sources
- Files:
-
- 14 edited
Legend:
- Unmodified
- Added
- Removed
-
trunk/sources/HeuristicLab.GP.StructureIdentification.Classification/3.3/DefaultClassificationAlgorithmOperators.cs
r2341 r2344 55 55 testAccuracy.GetVariableInfo("SamplesEnd").ActualName = "TestSamplesEnd"; 56 56 57 ConfusionMatrixEvaluator trainingConfusionMatrix = new ConfusionMatrixEvaluator();58 trainingConfusionMatrix.Name = "TrainingConfusionMatrixEvaluator";59 trainingConfusionMatrix.GetVariableInfo("ConfusionMatrix").ActualName = "TrainingConfusionMatrix";60 trainingConfusionMatrix.GetVariableInfo("SamplesStart").ActualName = "TrainingSamplesStart";61 trainingConfusionMatrix.GetVariableInfo("SamplesEnd").ActualName = "TrainingSamplesEnd";62 63 ConfusionMatrixEvaluator validationConfusionMatrix = new ConfusionMatrixEvaluator();64 validationConfusionMatrix.Name = "ValidationConfusionMatrixEvaluator";65 validationConfusionMatrix.GetVariableInfo("ConfusionMatrix").ActualName = "ValidationConfusionMatrix";66 validationConfusionMatrix.GetVariableInfo("SamplesStart").ActualName = "ValidationSamplesStart";67 validationConfusionMatrix.GetVariableInfo("SamplesEnd").ActualName = "ValidationSamplesEnd";68 69 ConfusionMatrixEvaluator testConfusionMatrix = new ConfusionMatrixEvaluator();70 testConfusionMatrix.Name = "TestConfusionMatrixEvaluator";71 testConfusionMatrix.GetVariableInfo("ConfusionMatrix").ActualName = "TestConfusionMatrix";72 testConfusionMatrix.GetVariableInfo("SamplesStart").ActualName = "TestSamplesStart";73 testConfusionMatrix.GetVariableInfo("SamplesEnd").ActualName = "TestSamplesEnd";74 75 57 individualProc.AddSubOperator(trainingAccuracy); 76 58 individualProc.AddSubOperator(validationAccuracy); 77 59 individualProc.AddSubOperator(testAccuracy); 78 individualProc.AddSubOperator(trainingConfusionMatrix);79 individualProc.AddSubOperator(validationConfusionMatrix);80 individualProc.AddSubOperator(testConfusionMatrix);81 60 return seq; 82 61 } … … 92 71 return op; 93 72 } 73 74 internal static void SetModelData(IAnalyzerModel model, IScope scope) { 75 model.SetResult("TrainingAccuracy", scope.GetVariableValue<DoubleData>("TrainingAccuracy", true).Data); 76 model.SetResult("ValidationAccuracy", scope.GetVariableValue<DoubleData>("ValidationAccuracy", true).Data); 77 model.SetResult("TestAccuracy", scope.GetVariableValue<DoubleData>("TestAccuracy", true).Data); 78 } 94 79 } 95 80 } -
trunk/sources/HeuristicLab.GP.StructureIdentification.Classification/3.3/OffspringSelectionGP.cs
r2341 r2344 34 34 return DefaultClassificationAlgorithmOperators.CreatePostProcessingOperator(); 35 35 } 36 37 protected override IAnalyzerModel CreateGPModel() { 38 IAnalyzerModel model = base.CreateGPModel(); 39 DefaultClassificationAlgorithmOperators.SetModelData(model, Engine.GlobalScope.SubScopes[0]); 40 return model; 41 } 36 42 } 37 43 } -
trunk/sources/HeuristicLab.GP.StructureIdentification.Classification/3.3/StandardGP.cs
r2341 r2344 27 27 namespace HeuristicLab.GP.StructureIdentification.Classification { 28 28 public class StandardGP : HeuristicLab.GP.StructureIdentification.StandardGP, IClassificationAlgorithm { 29 protected override IOperator CreateProblemInjector() { 30 return DefaultClassificationAlgorithmOperators.CreateProblemInjector(); 31 } 32 29 33 protected override IOperator CreatePostProcessingOperator() { 30 34 return DefaultClassificationAlgorithmOperators.CreatePostProcessingOperator(); 35 } 36 37 protected override IAnalyzerModel CreateGPModel() { 38 IAnalyzerModel model = base.CreateGPModel(); 39 DefaultClassificationAlgorithmOperators.SetModelData(model, Engine.GlobalScope.SubScopes[0]); 40 return model; 31 41 } 32 42 } -
trunk/sources/HeuristicLab.GP.StructureIdentification.TimeSeries/3.3/DefaultTimeSeriesOperators.cs
r2341 r2344 94 94 return seq; 95 95 } 96 97 internal static void SetModelData(IAnalyzerModel model, IScope scope) { 98 model.SetResult("TrainingTheilInequalityCoefficient", scope.GetVariableValue<DoubleData>("TrainingTheilInequalityCoefficient", true).Data); 99 model.SetResult("ValidationTheilInequalityCoefficient", scope.GetVariableValue<DoubleData>("ValidationTheilInequalityCoefficient", true).Data); 100 model.SetResult("TestTheilInequalityCoefficient", scope.GetVariableValue<DoubleData>("TestTheilInequalityCoefficient", true).Data); 101 } 96 102 } 97 103 } -
trunk/sources/HeuristicLab.GP.StructureIdentification.TimeSeries/3.3/OffspringSelectionGP.cs
r2341 r2344 65 65 } 66 66 67 protected override IAnalyzerModel CreateGPModel() { 68 IAnalyzerModel model = base.CreateGPModel(); 69 DefaultTimeSeriesOperators.SetModelData(model, Engine.GlobalScope.SubScopes[0]); 70 return model; 71 } 67 72 } 68 73 } -
trunk/sources/HeuristicLab.GP.StructureIdentification.TimeSeries/3.3/StandardGP.cs
r2341 r2344 63 63 return injector; 64 64 } 65 66 protected override IAnalyzerModel CreateGPModel() { 67 IAnalyzerModel model = base.CreateGPModel(); 68 DefaultTimeSeriesOperators.SetModelData(model, Engine.GlobalScope.SubScopes[0]); 69 return model; 70 } 65 71 } 66 72 } -
trunk/sources/HeuristicLab.GP.StructureIdentification/3.3/DefaultStructureIdentificationOperators.cs
r2341 r2344 282 282 model.TestSamplesEnd = bestModelScope.GetVariableValue<IntData>("TestSamplesEnd", true).Data; 283 283 284 model.TrainingMeanSquaredError = bestModelScope.GetVariableValue<DoubleData>("TrainingMSE", false).Data; 285 model.ValidationMeanSquaredError = bestModelScope.GetVariableValue<DoubleData>("ValidationMSE", false).Data; 286 model.TestMeanSquaredError = bestModelScope.GetVariableValue<DoubleData>("TestMSE", false).Data; 287 model.TrainingCoefficientOfDetermination = bestModelScope.GetVariableValue<DoubleData>("TrainingR2", false).Data; 288 model.ValidationCoefficientOfDetermination = bestModelScope.GetVariableValue<DoubleData>("ValidationR2", false).Data; 289 model.TestCoefficientOfDetermination = bestModelScope.GetVariableValue<DoubleData>("TestR2", false).Data; 290 model.TrainingMeanAbsolutePercentageError = bestModelScope.GetVariableValue<DoubleData>("TrainingMAPE", false).Data; 291 model.ValidationMeanAbsolutePercentageError = bestModelScope.GetVariableValue<DoubleData>("ValidationMAPE", false).Data; 292 model.TestMeanAbsolutePercentageError = bestModelScope.GetVariableValue<DoubleData>("TestMAPE", false).Data; 293 model.TrainingMeanAbsolutePercentageOfRangeError = bestModelScope.GetVariableValue<DoubleData>("TrainingMAPRE", false).Data; 294 model.ValidationMeanAbsolutePercentageOfRangeError = bestModelScope.GetVariableValue<DoubleData>("ValidationMAPRE", false).Data; 295 model.TestMeanAbsolutePercentageOfRangeError = bestModelScope.GetVariableValue<DoubleData>("TestMAPRE", false).Data; 296 model.TrainingVarianceAccountedFor = bestModelScope.GetVariableValue<DoubleData>("TrainingVAF", false).Data; 297 model.ValidationVarianceAccountedFor = bestModelScope.GetVariableValue<DoubleData>("ValidationVAF", false).Data; 298 model.TestVarianceAccountedFor = bestModelScope.GetVariableValue<DoubleData>("TestVAF", false).Data; 284 model.SetResult("TrainingMeanSquaredError", bestModelScope.GetVariableValue<DoubleData>("TrainingMSE", false).Data); 285 model.SetResult("ValidationMeanSquaredError", bestModelScope.GetVariableValue<DoubleData>("ValidationMSE", false).Data); 286 model.SetResult("TestMeanSquaredError", bestModelScope.GetVariableValue<DoubleData>("TestMSE", false).Data); 287 model.SetResult("TrainingCoefficientOfDetermination", bestModelScope.GetVariableValue<DoubleData>("TrainingR2", false).Data); 288 model.SetResult("ValidationCoefficientOfDetermination", bestModelScope.GetVariableValue<DoubleData>("ValidationR2", false).Data); 289 model.SetResult("TestCoefficientOfDetermination", bestModelScope.GetVariableValue<DoubleData>("TestR2", false).Data); 290 model.SetResult("TrainingMeanAbsolutePercentageError", bestModelScope.GetVariableValue<DoubleData>("TrainingMAPE", false).Data); 291 model.SetResult("ValidationMeanAbsolutePercentageError", bestModelScope.GetVariableValue<DoubleData>("ValidationMAPE", false).Data); 292 model.SetResult("TestMeanAbsolutePercentageError", bestModelScope.GetVariableValue<DoubleData>("TestMAPE", false).Data); 293 model.SetResult("TrainingMeanAbsolutePercentageOfRangeError", bestModelScope.GetVariableValue<DoubleData>("TrainingMAPRE", false).Data); 294 model.SetResult("ValidationMeanAbsolutePercentageOfRangeError", bestModelScope.GetVariableValue<DoubleData>("ValidationMAPRE", false).Data); 295 model.SetResult("TestMeanAbsolutePercentageOfRangeError", bestModelScope.GetVariableValue<DoubleData>("TestMAPRE", false).Data); 296 model.SetResult("TrainingVarianceAccountedFor", bestModelScope.GetVariableValue<DoubleData>("TrainingVAF", false).Data); 297 model.SetResult("ValidationVarianceAccountedFor", bestModelScope.GetVariableValue<DoubleData>("ValidationVAF", false).Data); 298 model.SetResult("TestVarianceAccountedFor", bestModelScope.GetVariableValue<DoubleData>("TestVAF", false).Data); 299 300 model.SetMetaData("EvaluatedSolutions", bestModelScope.GetVariableValue<DoubleData>("EvaluatedSolutions", true).Data); 301 IGeneticProgrammingModel gpModel = bestModelScope.GetVariableValue<IGeneticProgrammingModel>("FunctionTree", true); 302 model.SetMetaData("TreeSize", gpModel.Size); 303 model.SetMetaData("TreeHeight", gpModel.Height); 299 304 300 305 ItemList evaluationImpacts = bestModelScope.GetVariableValue<ItemList>("VariableEvaluationImpacts", false); -
trunk/sources/HeuristicLab.GP.StructureIdentification/3.3/OffspringSelectionGP.cs
r2341 r2344 146 146 } 147 147 148 pr ivateIAnalyzerModel CreateGPModel() {148 protected virtual IAnalyzerModel CreateGPModel() { 149 149 IScope bestModelScope = Engine.GlobalScope.SubScopes[0]; 150 return DefaultStructureIdentificationAlgorithmOperators.CreateGPModel(bestModelScope); 150 IAnalyzerModel model = DefaultStructureIdentificationAlgorithmOperators.CreateGPModel(bestModelScope); 151 model.SetMetaData("SelectionPressure", bestModelScope.GetVariableValue<DoubleData>("SelectionPressure", true).Data); 152 return model; 151 153 } 152 154 } -
trunk/sources/HeuristicLab.GP.StructureIdentification/3.3/StandardGP.cs
r2341 r2344 145 145 } 146 146 147 pr ivateIAnalyzerModel CreateGPModel() {147 protected virtual IAnalyzerModel CreateGPModel() { 148 148 IScope bestModelScope = Engine.GlobalScope.SubScopes[0]; 149 return DefaultStructureIdentificationAlgorithmOperators.CreateGPModel(bestModelScope); 149 IAnalyzerModel model = DefaultStructureIdentificationAlgorithmOperators.CreateGPModel(bestModelScope); 150 return model; 150 151 } 151 152 } -
trunk/sources/HeuristicLab.LinearRegression/3.2/LinearRegression.cs
r2341 r2344 276 276 IAnalyzerModel model = new AnalyzerModel(); 277 277 model.Predictor = bestModelScope.GetVariableValue<IPredictor>("Predictor", true); 278 model.TrainingMeanSquaredError = bestModelScope.GetVariableValue<DoubleData>("TrainingQuality", false).Data; 279 model.ValidationMeanSquaredError = bestModelScope.GetVariableValue<DoubleData>("ValidationQuality", false).Data; 280 model.TestMeanSquaredError = bestModelScope.GetVariableValue<DoubleData>("TestQuality", false).Data; 281 model.TrainingCoefficientOfDetermination = bestModelScope.GetVariableValue<DoubleData>("TrainingR2", false).Data; 282 model.ValidationCoefficientOfDetermination = bestModelScope.GetVariableValue<DoubleData>("ValidationR2", false).Data; 283 model.TestCoefficientOfDetermination = bestModelScope.GetVariableValue<DoubleData>("TestR2", false).Data; 284 model.TrainingMeanAbsolutePercentageError = bestModelScope.GetVariableValue<DoubleData>("TrainingMAPE", false).Data; 285 model.ValidationMeanAbsolutePercentageError = bestModelScope.GetVariableValue<DoubleData>("ValidationMAPE", false).Data; 286 model.TestMeanAbsolutePercentageError = bestModelScope.GetVariableValue<DoubleData>("TestMAPE", false).Data; 287 model.TrainingMeanAbsolutePercentageOfRangeError = bestModelScope.GetVariableValue<DoubleData>("TrainingMAPRE", false).Data; 288 model.ValidationMeanAbsolutePercentageOfRangeError = bestModelScope.GetVariableValue<DoubleData>("ValidationMAPRE", false).Data; 289 model.TestMeanAbsolutePercentageOfRangeError = bestModelScope.GetVariableValue<DoubleData>("TestMAPRE", false).Data; 290 model.TrainingVarianceAccountedFor = bestModelScope.GetVariableValue<DoubleData>("TrainingVAF", false).Data; 291 model.ValidationVarianceAccountedFor = bestModelScope.GetVariableValue<DoubleData>("ValidationVAF", false).Data; 292 model.TestVarianceAccountedFor = bestModelScope.GetVariableValue<DoubleData>("TestVAF", false).Data; 278 model.SetResult("TrainingMeanSquaredError", bestModelScope.GetVariableValue<DoubleData>("TrainingQuality", false).Data); 279 model.SetResult("ValidationMeanSquaredError", bestModelScope.GetVariableValue<DoubleData>("ValidationQuality", false).Data); 280 model.SetResult("TestMeanSquaredError", bestModelScope.GetVariableValue<DoubleData>("TestQuality", false).Data); 281 model.SetResult("TrainingCoefficientOfDetermination", bestModelScope.GetVariableValue<DoubleData>("TrainingR2", false).Data); 282 model.SetResult("ValidationCoefficientOfDetermination", bestModelScope.GetVariableValue<DoubleData>("ValidationR2", false).Data); 283 model.SetResult("TestCoefficientOfDetermination", bestModelScope.GetVariableValue<DoubleData>("TestR2", false).Data); 284 model.SetResult("TrainingMeanAbsolutePercentageError", bestModelScope.GetVariableValue<DoubleData>("TrainingMAPE", false).Data); 285 model.SetResult("ValidationMeanAbsolutePercentageError", bestModelScope.GetVariableValue<DoubleData>("ValidationMAPE", false).Data); 286 model.SetResult("TestMeanAbsolutePercentageError", bestModelScope.GetVariableValue<DoubleData>("TestMAPE", false).Data); 287 model.SetResult("TrainingMeanAbsolutePercentageOfRangeError", bestModelScope.GetVariableValue<DoubleData>("TrainingMAPRE", false).Data); 288 model.SetResult("ValidationMeanAbsolutePercentageOfRangeError", bestModelScope.GetVariableValue<DoubleData>("ValidationMAPRE", false).Data); 289 model.SetResult("TestMeanAbsolutePercentageOfRangeError", bestModelScope.GetVariableValue<DoubleData>("TestMAPRE", false).Data); 290 model.SetResult("TrainingVarianceAccountedFor", bestModelScope.GetVariableValue<DoubleData>("TrainingVAF", false).Data); 291 model.SetResult("ValidationVarianceAccountedFor", bestModelScope.GetVariableValue<DoubleData>("ValidationVAF", false).Data); 292 model.SetResult("TestVarianceAccountedFor", bestModelScope.GetVariableValue<DoubleData>("TestVAF", false).Data); 293 294 IGeneticProgrammingModel gpModel = bestModelScope.GetVariableValue<IGeneticProgrammingModel>("LinearRegressionModel", false); 295 model.SetMetaData("TreeSize", gpModel.Size); 296 model.SetMetaData("TreeHeight", gpModel.Height); 293 297 294 298 HeuristicLab.DataAnalysis.Dataset ds = bestModelScope.GetVariableValue<Dataset>("Dataset", true); -
trunk/sources/HeuristicLab.Modeling.Database.SQLServerCompact/3.2/DatabaseService.cs
r2339 r2344 38 38 Connect(); 39 39 if (!ctx.DatabaseExists()) 40 ctx.CreateDatabase(); 40 ctx.CreateDatabase(); 41 41 } 42 42 … … 109 109 110 110 using (ModelingDataContext ctx = new ModelingDataContext(connection)) { 111 //get all double properties to save as modelResult 112 IEnumerable<PropertyInfo> modelResultInfos = model.GetType().GetProperties().Where( 113 info => info.PropertyType == typeof(double)); 114 foreach (PropertyInfo modelResultInfo in modelResultInfos) { 115 Result result = GetOrCreateResult(modelResultInfo.Name); 116 double value = (double)modelResultInfo.GetValue(model, null); 117 ctx.ModelResults.InsertOnSubmit(new ModelResult(m, result, value)); 111 foreach (KeyValuePair<string, double> pair in model.Results) { 112 Result result = GetOrCreateResult(pair.Key); 113 ctx.ModelResults.InsertOnSubmit(new ModelResult(m, result, pair.Value)); 118 114 } 119 115 ctx.SubmitChanges(); 120 116 } 117 118 // code to store meta-information for models (gkronber (8.9.09)) 119 //using (ModelingDataContext ctx = new ModelingDataContext(connection)) { 120 // foreach (KeyValuePair<string, double> pair in model.MetaData) { 121 // MetaData metaData = GetOrCreateMetaData(pair.Key); 122 // ctx.ModelMetaData.InsertOnSubmit(new ModelMetaData(m, metaData, pair.Value)); 123 // } 124 // ctx.SubmitChanges(); 125 //} 121 126 122 127 using (ModelingDataContext ctx = new ModelingDataContext(connection)) { -
trunk/sources/HeuristicLab.Modeling/3.2/AnalyzerModel.cs
r2285 r2344 61 61 } 62 62 63 private double trainingMSE; 64 public double TrainingMeanSquaredError { 65 get { return trainingMSE; } 66 set { trainingMSE = value; } 63 private Dictionary<string, double> results = new Dictionary<string, double>(); 64 public IEnumerable<KeyValuePair<string, double>> Results { 65 get { return results; } 67 66 } 68 67 69 private double validationMSE; 70 public double ValidationMeanSquaredError { 71 get { return validationMSE; } 72 set { validationMSE = value; } 68 public void SetResult(string name, double value) { 69 results.Add(name, value); 73 70 } 74 71 75 private double testMSE; 76 public double TestMeanSquaredError { 77 get { return testMSE; } 78 set { testMSE = value; } 72 public double GetResult(string name) { 73 return results[name]; 79 74 } 80 75 81 p ublic double TrainingMeanAbsolutePercentageError {82 get;83 set;76 private Dictionary<string, object> metadata = new Dictionary<string, object>(); 77 public IEnumerable<KeyValuePair<string, object>> MetaData { 78 get { return metadata; } 84 79 } 85 80 86 public double ValidationMeanAbsolutePercentageError { 87 get; 88 set; 81 public void SetMetaData(string name, object value) { 82 metadata.Add(name, value); 89 83 } 90 84 91 public double TestMeanAbsolutePercentageError { 92 get; 93 set; 94 } 95 96 public double TrainingMeanAbsolutePercentageOfRangeError { 97 get; 98 set; 99 } 100 101 public double ValidationMeanAbsolutePercentageOfRangeError { 102 get; 103 set; 104 } 105 106 public double TestMeanAbsolutePercentageOfRangeError { 107 get; 108 set; 109 } 110 111 public double TrainingCoefficientOfDetermination { 112 get; 113 set; 114 } 115 116 public double ValidationCoefficientOfDetermination { 117 get; 118 set; 119 } 120 121 public double TestCoefficientOfDetermination { 122 get; 123 set; 124 } 125 126 public double TrainingVarianceAccountedFor { 127 get; 128 set; 129 } 130 131 public double ValidationVarianceAccountedFor { 132 get; 133 set; 134 } 135 136 public double TestVarianceAccountedFor { 137 get; 138 set; 85 public object GetMetaData(string name) { 86 return metadata[name]; 139 87 } 140 88 -
trunk/sources/HeuristicLab.Modeling/3.2/IAnalyzerModel.cs
r2285 r2344 27 27 28 28 namespace HeuristicLab.Modeling { 29 public interface IAnalyzerModel { 29 public interface IAnalyzerModel { 30 IPredictor Predictor { get; set; } 30 31 Dataset Dataset { get; set; } 31 32 string TargetVariable { get; set; } 32 33 IEnumerable<string> InputVariables { get; } 34 IEnumerable<KeyValuePair<string, double>> Results { get; } 35 IEnumerable<KeyValuePair<string, object>> MetaData { get; } 33 36 int TrainingSamplesStart { get; set; } 34 37 int TrainingSamplesEnd { get; set; } … … 37 40 int TestSamplesStart { get; set; } 38 41 int TestSamplesEnd { get; set; } 39 double TrainingMeanSquaredError { get; set; } 40 double ValidationMeanSquaredError { get; set; } 41 double TestMeanSquaredError { get; set; } 42 double TrainingMeanAbsolutePercentageError { get; set; } 43 double ValidationMeanAbsolutePercentageError { get; set; } 44 double TestMeanAbsolutePercentageError { get; set; } 45 double TrainingMeanAbsolutePercentageOfRangeError { get; set; } 46 double ValidationMeanAbsolutePercentageOfRangeError { get; set; } 47 double TestMeanAbsolutePercentageOfRangeError { get; set; } 48 double TrainingCoefficientOfDetermination { get; set; } 49 double ValidationCoefficientOfDetermination { get; set; } 50 double TestCoefficientOfDetermination { get; set; } 51 double TrainingVarianceAccountedFor { get; set; } 52 double ValidationVarianceAccountedFor { get; set; } 53 double TestVarianceAccountedFor { get; set; } 42 void SetResult(string name, double value); 43 double GetResult(string name); 44 void SetMetaData(string name, object data); 45 object GetMetaData(string name); 54 46 double GetVariableEvaluationImpact(string variableName); 55 47 double GetVariableQualityImpact(string variableName); … … 57 49 void SetVariableEvaluationImpact(string variableName, double impact); 58 50 void SetVariableQualityImpact(string variableName, double impact); 59 IPredictor Predictor { get; set; }60 51 } 61 52 } -
trunk/sources/HeuristicLab.SupportVectorMachines/3.2/SupportVectorRegression.cs
r2328 r2344 412 412 qualImpactCalc.GetVariableInfo("SamplesStart").ActualName = "ActualTrainingSamplesStart"; 413 413 qualImpactCalc.GetVariableInfo("SamplesEnd").ActualName = "ActualTrainingSamplesEnd"; 414 414 415 415 seqProc.AddSubOperator(predictorBuilder); 416 416 seqProc.AddSubOperator(evalImpactCalc); … … 425 425 protected internal virtual IAnalyzerModel CreateSVMModel(IScope bestModelScope) { 426 426 AnalyzerModel model = new AnalyzerModel(); 427 model.TrainingMeanSquaredError = bestModelScope.GetVariableValue<DoubleData>("Quality", false).Data; 428 model.ValidationMeanSquaredError = bestModelScope.GetVariableValue<DoubleData>("ValidationQuality", false).Data; 429 model.TestMeanSquaredError = bestModelScope.GetVariableValue<DoubleData>("TestQuality", false).Data; 430 model.TrainingCoefficientOfDetermination = bestModelScope.GetVariableValue<DoubleData>("ActualTrainingR2", false).Data; 431 model.ValidationCoefficientOfDetermination = bestModelScope.GetVariableValue<DoubleData>("ValidationR2", false).Data; 432 model.TestCoefficientOfDetermination = bestModelScope.GetVariableValue<DoubleData>("TestR2", false).Data; 433 model.TrainingMeanAbsolutePercentageError = bestModelScope.GetVariableValue<DoubleData>("ActualTrainingMAPE", false).Data; 434 model.ValidationMeanAbsolutePercentageError = bestModelScope.GetVariableValue<DoubleData>("ValidationMAPE", false).Data; 435 model.TestMeanAbsolutePercentageError = bestModelScope.GetVariableValue<DoubleData>("TestMAPE", false).Data; 436 model.TrainingMeanAbsolutePercentageOfRangeError = bestModelScope.GetVariableValue<DoubleData>("ActualTrainingMAPRE", false).Data; 437 model.ValidationMeanAbsolutePercentageOfRangeError = bestModelScope.GetVariableValue<DoubleData>("ValidationMAPRE", false).Data; 438 model.TestMeanAbsolutePercentageOfRangeError = bestModelScope.GetVariableValue<DoubleData>("TestMAPRE", false).Data; 439 model.TrainingVarianceAccountedFor = bestModelScope.GetVariableValue<DoubleData>("ActualTrainingVAF", false).Data; 440 model.ValidationVarianceAccountedFor = bestModelScope.GetVariableValue<DoubleData>("ValidationVAF", false).Data; 441 model.TestVarianceAccountedFor = bestModelScope.GetVariableValue<DoubleData>("TestVAF", false).Data; 427 model.SetResult("TrainingMeanSquaredError", bestModelScope.GetVariableValue<DoubleData>("Quality", false).Data); 428 model.SetResult("ValidationMeanSquaredError", bestModelScope.GetVariableValue<DoubleData>("ValidationQuality", false).Data); 429 model.SetResult("TestMeanSquaredError", bestModelScope.GetVariableValue<DoubleData>("TestQuality", false).Data); 430 model.SetResult("TrainingCoefficientOfDetermination", bestModelScope.GetVariableValue<DoubleData>("ActualTrainingR2", false).Data); 431 model.SetResult("ValidationCoefficientOfDetermination", bestModelScope.GetVariableValue<DoubleData>("ValidationR2", false).Data); 432 model.SetResult("TestCoefficientOfDetermination", bestModelScope.GetVariableValue<DoubleData>("TestR2", false).Data); 433 model.SetResult("TrainingMeanAbsolutePercentageError", bestModelScope.GetVariableValue<DoubleData>("ActualTrainingMAPE", false).Data); 434 model.SetResult("ValidationMeanAbsolutePercentageError", bestModelScope.GetVariableValue<DoubleData>("ValidationMAPE", false).Data); 435 model.SetResult("TestMeanAbsolutePercentageError", bestModelScope.GetVariableValue<DoubleData>("TestMAPE", false).Data); 436 model.SetResult("TrainingMeanAbsolutePercentageOfRangeError", bestModelScope.GetVariableValue<DoubleData>("ActualTrainingMAPRE", false).Data); 437 model.SetResult("ValidationMeanAbsolutePercentageOfRangeError", bestModelScope.GetVariableValue<DoubleData>("ValidationMAPRE", false).Data); 438 model.SetResult("TestMeanAbsolutePercentageOfRangeError", bestModelScope.GetVariableValue<DoubleData>("TestMAPRE", false).Data); 439 model.SetResult("TrainingVarianceAccountedFor", bestModelScope.GetVariableValue<DoubleData>("ActualTrainingVAF", false).Data); 440 model.SetResult("ValidationVarianceAccountedFor", bestModelScope.GetVariableValue<DoubleData>("ValidationVAF", false).Data); 441 model.SetResult("TestVarianceAccountedFor", bestModelScope.GetVariableValue<DoubleData>("TestVAF", false).Data); 442 443 model.SetMetaData("Cost", bestModelScope.GetVariableValue<DoubleData>("Cost", false).Data); 444 model.SetMetaData("Nu", bestModelScope.GetVariableValue<DoubleData>("Nu", false).Data); 442 445 443 446 HeuristicLab.DataAnalysis.Dataset ds = bestModelScope.GetVariableValue<Dataset>("Dataset", true);
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