- Timestamp:
- 04/02/12 10:55:26 (12 years ago)
- Location:
- branches/ProblemInstancesRegressionAndClassification
- Files:
-
- 20 added
- 58 edited
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- Unmodified
- Added
- Removed
-
branches/ProblemInstancesRegressionAndClassification/HeuristicLab 3.3.sln
r7666 r7682 19 19 EndProject 20 20 Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "HeuristicLab.Problems.Instances.Views-3.4", "HeuristicLab.Problems.Instances.Views\3.4\HeuristicLab.Problems.Instances.Views-3.4.csproj", "{B1BA398F-953F-4C3A-B07B-1E5E17A27DD9}" 21 EndProject 22 Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "HeuristicLab.Problems.Instances.Classification-3.4", "HeuristicLab.Problems.Instances.Classification\3.4\HeuristicLab.Problems.Instances.Classification-3.4.csproj", "{1BBFCD5B-8A1C-4225-A682-ADEC7800E683}" 21 23 EndProject 22 24 Global … … 120 122 {B1BA398F-953F-4C3A-B07B-1E5E17A27DD9}.Release|x64.ActiveCfg = Release|Any CPU 121 123 {B1BA398F-953F-4C3A-B07B-1E5E17A27DD9}.Release|x86.ActiveCfg = Release|Any CPU 124 {1BBFCD5B-8A1C-4225-A682-ADEC7800E683}.Debug|Any CPU.ActiveCfg = Debug|Any CPU 125 {1BBFCD5B-8A1C-4225-A682-ADEC7800E683}.Debug|Any CPU.Build.0 = Debug|Any CPU 126 {1BBFCD5B-8A1C-4225-A682-ADEC7800E683}.Debug|Mixed Platforms.ActiveCfg = Debug|Any CPU 127 {1BBFCD5B-8A1C-4225-A682-ADEC7800E683}.Debug|Mixed Platforms.Build.0 = Debug|Any CPU 128 {1BBFCD5B-8A1C-4225-A682-ADEC7800E683}.Debug|x64.ActiveCfg = Debug|Any CPU 129 {1BBFCD5B-8A1C-4225-A682-ADEC7800E683}.Debug|x86.ActiveCfg = Debug|Any CPU 130 {1BBFCD5B-8A1C-4225-A682-ADEC7800E683}.Release|Any CPU.ActiveCfg = Release|Any CPU 131 {1BBFCD5B-8A1C-4225-A682-ADEC7800E683}.Release|Any CPU.Build.0 = Release|Any CPU 132 {1BBFCD5B-8A1C-4225-A682-ADEC7800E683}.Release|Mixed Platforms.ActiveCfg = Release|Any CPU 133 {1BBFCD5B-8A1C-4225-A682-ADEC7800E683}.Release|Mixed Platforms.Build.0 = Release|Any CPU 134 {1BBFCD5B-8A1C-4225-A682-ADEC7800E683}.Release|x64.ActiveCfg = Release|Any CPU 135 {1BBFCD5B-8A1C-4225-A682-ADEC7800E683}.Release|x86.ActiveCfg = Release|Any CPU 122 136 EndGlobalSection 123 137 GlobalSection(SolutionProperties) = preSolution -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/ClassificationProblem.cs
r7259 r7682 20 20 #endregion 21 21 22 using System; 23 using System.Collections.Generic; 24 using System.Linq; 22 25 using HeuristicLab.Common; 23 26 using HeuristicLab.Core; 24 27 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable; 28 using HeuristicLab.Problems.Instances; 25 29 26 30 namespace HeuristicLab.Problems.DataAnalysis { … … 28 32 [Item("Classification Problem", "A general classification problem.")] 29 33 [Creatable("Problems")] 30 public class ClassificationProblem : DataAnalysisProblem<IClassificationProblemData>, IClassificationProblem, IStorableContent { 34 public class ClassificationProblem : DataAnalysisProblem<IClassificationProblemData>, IClassificationProblem, IStorableContent, 35 IProblemInstanceConsumer<ClassificationData>, IProblemInstanceExporter<ClassificationData>, IProblemInstanceConsumer { 31 36 public string Filename { get; set; } 32 37 … … 45 50 ProblemData = problemData; 46 51 } 52 53 public void Load(ClassificationData data) { 54 Name = data.Name; 55 Description = data.Description; 56 Dataset dataset = new Dataset(data.InputVariables, data.Values); 57 ProblemData = new ClassificationProblemData(dataset, data.AllowedInputVariables, data.TargetVariable); 58 ProblemData.TrainingPartition.Start = data.TrainingPartitionStart; 59 ProblemData.TrainingPartition.End = data.TrainingPartitionEnd; 60 ProblemData.TestPartition.Start = data.TestPartitionStart; 61 ProblemData.TestPartition.End = data.TestPartitionEnd; 62 OnReset(); 63 } 64 65 public ClassificationData Export() { 66 if (!ProblemData.InputVariables.Count.Equals(ProblemData.Dataset.DoubleVariables.Count())) 67 throw new ArgumentException("Not all input variables are double variables! (Export only works with double variables)"); 68 69 ClassificationData claData = new ClassificationData(); 70 claData.Name = Name; 71 claData.Description = Description; 72 claData.TargetVariable = ProblemData.TargetVariable; 73 claData.InputVariables = ProblemData.InputVariables.Select(x => x.Value).ToArray(); 74 claData.AllowedInputVariables = ProblemData.AllowedInputVariables.ToArray(); 75 claData.TrainingPartitionStart = ProblemData.TrainingPartition.Start; 76 claData.TrainingPartitionEnd = ProblemData.TrainingPartition.End; 77 claData.TestPartitionStart = ProblemData.TestPartition.Start; 78 claData.TestPartitionEnd = ProblemData.TestPartition.End; 79 80 List<List<double>> data = new List<List<double>>(); 81 foreach (var variable in ProblemData.Dataset.DoubleVariables) { 82 data.Add(ProblemData.Dataset.GetDoubleValues(variable).ToList()); 83 } 84 claData.Values = Transformer.Transformation(data); 85 86 return claData; 87 } 47 88 } 48 89 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Regression/RegressionProblem.cs
r7664 r7682 71 71 regData.Description = Description; 72 72 regData.TargetVariable = ProblemData.TargetVariable; 73 regData.InputVariables = ProblemData.InputVariables.Select(x => x.Value) ;74 regData.AllowedInputVariables = ProblemData.AllowedInputVariables ;73 regData.InputVariables = ProblemData.InputVariables.Select(x => x.Value).ToArray(); 74 regData.AllowedInputVariables = ProblemData.AllowedInputVariables.ToArray(); 75 75 regData.TrainingPartitionStart = ProblemData.TrainingPartition.Start; 76 76 regData.TrainingPartitionEnd = ProblemData.TrainingPartition.End; … … 82 82 data.Add(ProblemData.Dataset.GetDoubleValues(variable).ToList()); 83 83 } 84 regData.Values = Transform ation(data);84 regData.Values = Transformer.Transformation(data); 85 85 86 86 return regData; 87 87 } 88 89 public static double[,] Transformation(List<List<double>> data) {90 if (!data.All(x => x.Count.Equals(data.First().Count)))91 throw new ArgumentException("Can't create jagged array.");92 double[,] values = new double[data.First().Count, data.Count];93 for (int i = 0; i < values.GetLength(0); i++) {94 for (int j = 0; j < values.GetLength(1); j++) {95 values[i, j] = data[j][i];96 }97 }98 return values;99 }100 88 } 101 89 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/ArtificialRegressionDataDescriptor.cs
r7664 r7682 20 20 #endregion 21 21 22 23 22 using System.Collections.Generic; 24 23 namespace HeuristicLab.Problems.Instances.Regression { … … 28 27 29 28 protected abstract string TargetVariable { get; } 30 protected abstract IEnumerable<string>InputVariables { get; }31 protected abstract IEnumerable<string>AllowedInputVariables { get; }29 protected abstract string[] InputVariables { get; } 30 protected abstract string[] AllowedInputVariables { get; } 32 31 protected abstract int TrainingPartitionStart { get; } 33 32 protected abstract int TrainingPartitionEnd { get; } … … 42 41 regData.AllowedInputVariables = this.AllowedInputVariables; 43 42 regData.TargetVariable = this.TargetVariable; 44 regData.Values = this.GenerateValues();43 regData.Values = Transformer.Transformation(this.GenerateValues()); 45 44 regData.TrainingPartitionStart = this.TrainingPartitionStart; 46 45 regData.TrainingPartitionEnd = this.TrainingPartitionEnd; … … 50 49 } 51 50 52 protected abstract double[,]GenerateValues();51 protected abstract List<List<double>> GenerateValues(); 53 52 } 54 53 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Keijzer/KeijzerFunctionEight.cs
r7664 r7682 39 39 } 40 40 protected override string TargetVariable { get { return "F"; } } 41 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X", "F" }; } }42 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X" }; } }41 protected override string[] InputVariables { get { return new string[] { "X", "F" }; } } 42 protected override string[] AllowedInputVariables { get { return new string[] { "X" }; } } 43 43 protected override int TrainingPartitionStart { get { return 0; } } 44 44 protected override int TrainingPartitionEnd { get { return 100; } } … … 46 46 protected override int TestPartitionEnd { get { return 1091; } } 47 47 48 protected override double[,]GenerateValues() {48 protected override List<List<double>> GenerateValues() { 49 49 List<List<double>> data = new List<List<double>>(); 50 50 data.Add(ValueGenerator.GenerateSteps(1, 100, 1)); … … 59 59 data.Add(results); 60 60 61 return ValueGenerator.Transformation(data);61 return data; 62 62 } 63 63 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Keijzer/KeijzerFunctionFifteen.cs
r7664 r7682 41 41 } 42 42 protected override string TargetVariable { get { return "F"; } } 43 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X", "Y", "F" }; } }44 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X", "Y" }; } }43 protected override string[] InputVariables { get { return new string[] { "X", "Y", "F" }; } } 44 protected override string[] AllowedInputVariables { get { return new string[] { "X", "Y" }; } } 45 45 protected override int TrainingPartitionStart { get { return 0; } } 46 46 protected override int TrainingPartitionEnd { get { return 20; } } … … 48 48 protected override int TestPartitionEnd { get { return 5000; } } 49 49 50 protected override double[,]GenerateValues() {50 protected override List<List<double>> GenerateValues() { 51 51 List<List<double>> data = new List<List<double>>(); 52 52 for (int i = 0; i < AllowedInputVariables.Count(); i++) { … … 63 63 data.Add(results); 64 64 65 return ValueGenerator.Transformation(data);65 return data; 66 66 } 67 67 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Keijzer/KeijzerFunctionFour.cs
r7664 r7682 38 38 } 39 39 protected override string TargetVariable { get { return "F"; } } 40 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X", "F" }; } }41 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X" }; } }40 protected override string[] InputVariables { get { return new string[] { "X", "F" }; } } 41 protected override string[] AllowedInputVariables { get { return new string[] { "X" }; } } 42 42 protected override int TrainingPartitionStart { get { return 0; } } 43 43 protected override int TrainingPartitionEnd { get { return 21; } } … … 45 45 protected override int TestPartitionEnd { get { return 2022; } } 46 46 47 protected override double[,]GenerateValues() {47 protected override List<List<double>> GenerateValues() { 48 48 List<List<double>> data = new List<List<double>>(); 49 49 data.Add(ValueGenerator.GenerateSteps(-1, 1, 0.1)); … … 58 58 data.Add(results); 59 59 60 return ValueGenerator.Transformation(data);60 return data; 61 61 } 62 62 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Keijzer/KeijzerFunctionSeven.cs
r7664 r7682 39 39 } 40 40 protected override string TargetVariable { get { return "F"; } } 41 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X", "F" }; } }42 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X" }; } }41 protected override string[] InputVariables { get { return new string[] { "X", "F" }; } } 42 protected override string[] AllowedInputVariables { get { return new string[] { "X" }; } } 43 43 protected override int TrainingPartitionStart { get { return 0; } } 44 44 protected override int TrainingPartitionEnd { get { return 50; } } … … 46 46 protected override int TestPartitionEnd { get { return 170; } } 47 47 48 protected override double[,]GenerateValues() {48 protected override List<List<double>> GenerateValues() { 49 49 List<List<double>> data = new List<List<double>>(); 50 50 data.Add(ValueGenerator.GenerateSteps(1, 50, 1)); … … 59 59 data.Add(results); 60 60 61 return ValueGenerator.Transformation(data);61 return data; 62 62 } 63 63 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Keijzer/KeijzerFunctionSix.cs
r7664 r7682 38 38 } 39 39 protected override string TargetVariable { get { return "F"; } } 40 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X", "Y", "Z", "F" }; } }41 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X", "Y", "Z" }; } }40 protected override string[] InputVariables { get { return new string[] { "X", "Y", "Z", "F" }; } } 41 protected override string[] AllowedInputVariables { get { return new string[] { "X", "Y", "Z" }; } } 42 42 protected override int TrainingPartitionStart { get { return 0; } } 43 43 protected override int TrainingPartitionEnd { get { return 1000; } } … … 45 45 protected override int TestPartitionEnd { get { return 11000; } } 46 46 47 protected override double[,]GenerateValues() {47 protected override List<List<double>> GenerateValues() { 48 48 List<List<double>> data = new List<List<double>>(); 49 49 data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, -1, 1)); … … 61 61 data.Add(results); 62 62 63 return ValueGenerator.Transformation(data);63 return data; 64 64 } 65 65 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Keijzer/KeijzerFunctionSixteen.cs
r7664 r7682 41 41 } 42 42 protected override string TargetVariable { get { return "F"; } } 43 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X", "Y", "F" }; } }44 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X", "Y" }; } }43 protected override string[] InputVariables { get { return new string[] { "X", "Y", "F" }; } } 44 protected override string[] AllowedInputVariables { get { return new string[] { "X", "Y" }; } } 45 45 protected override int TrainingPartitionStart { get { return 0; } } 46 46 protected override int TrainingPartitionEnd { get { return 20; } } … … 48 48 protected override int TestPartitionEnd { get { return 5000; } } 49 49 50 protected override double[,]GenerateValues() {50 protected override List<List<double>> GenerateValues() { 51 51 List<List<double>> data = new List<List<double>>(); 52 52 for (int i = 0; i < AllowedInputVariables.Count(); i++) { … … 63 63 data.Add(results); 64 64 65 return ValueGenerator.Transformation(data);65 return data; 66 66 } 67 67 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Keijzer/KeijzerFunctionThirteen.cs
r7664 r7682 41 41 } 42 42 protected override string TargetVariable { get { return "F"; } } 43 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X", "Y", "F" }; } }44 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X", "Y" }; } }43 protected override string[] InputVariables { get { return new string[] { "X", "Y", "F" }; } } 44 protected override string[] AllowedInputVariables { get { return new string[] { "X", "Y" }; } } 45 45 protected override int TrainingPartitionStart { get { return 0; } } 46 46 protected override int TrainingPartitionEnd { get { return 20; } } … … 48 48 protected override int TestPartitionEnd { get { return 5000; } } 49 49 50 protected override double[,]GenerateValues() {50 protected override List<List<double>> GenerateValues() { 51 51 List<List<double>> data = new List<List<double>>(); 52 52 for (int i = 0; i < AllowedInputVariables.Count(); i++) { … … 63 63 data.Add(results); 64 64 65 return ValueGenerator.Transformation(data);65 return data; 66 66 } 67 67 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Keijzer/KeijzerFunctionTwelve.cs
r7664 r7682 41 41 } 42 42 protected override string TargetVariable { get { return "F"; } } 43 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X", "Y", "F" }; } }44 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X", "Y" }; } }43 protected override string[] InputVariables { get { return new string[] { "X", "Y", "F" }; } } 44 protected override string[] AllowedInputVariables { get { return new string[] { "X", "Y" }; } } 45 45 protected override int TrainingPartitionStart { get { return 0; } } 46 46 protected override int TrainingPartitionEnd { get { return 20; } } … … 48 48 protected override int TestPartitionEnd { get { return 5000; } } 49 49 50 protected override double[,]GenerateValues() {50 protected override List<List<double>> GenerateValues() { 51 51 List<List<double>> data = new List<List<double>>(); 52 52 for (int i = 0; i < AllowedInputVariables.Count(); i++) { … … 63 63 data.Add(results); 64 64 65 return ValueGenerator.Transformation(data);65 return data; 66 66 } 67 67 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Korns/KornsFunctionEight.cs
r7664 r7682 45 45 } 46 46 protected override string TargetVariable { get { return "Y"; } } 47 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X0", "X1", "X2", "X3", "X4", "Y" }; } }48 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X0", "X1", "X2", "X3", "X4" }; } }47 protected override string[] InputVariables { get { return new string[] { "X0", "X1", "X2", "X3", "X4", "Y" }; } } 48 protected override string[] AllowedInputVariables { get { return new string[] { "X0", "X1", "X2", "X3", "X4" }; } } 49 49 protected override int TrainingPartitionStart { get { return 0; } } 50 50 protected override int TrainingPartitionEnd { get { return 5000; } } … … 52 52 protected override int TestPartitionEnd { get { return 10000; } } 53 53 54 protected override double[,]GenerateValues() {54 protected override List<List<double>> GenerateValues() { 55 55 List<List<double>> data = new List<List<double>>(); 56 56 for (int i = 0; i < AllowedInputVariables.Count(); i++) { … … 68 68 data.Add(results); 69 69 70 return ValueGenerator.Transformation(data);70 return data; 71 71 } 72 72 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Korns/KornsFunctionEleven.cs
r7664 r7682 44 44 } 45 45 protected override string TargetVariable { get { return "Y"; } } 46 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X0", "X1", "X2", "X3", "X4", "Y" }; } }47 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X0", "X1", "X2", "X3", "X4" }; } }46 protected override string[] InputVariables { get { return new string[] { "X0", "X1", "X2", "X3", "X4", "Y" }; } } 47 protected override string[] AllowedInputVariables { get { return new string[] { "X0", "X1", "X2", "X3", "X4" }; } } 48 48 protected override int TrainingPartitionStart { get { return 0; } } 49 49 protected override int TrainingPartitionEnd { get { return 5000; } } … … 51 51 protected override int TestPartitionEnd { get { return 10000; } } 52 52 53 protected override double[,]GenerateValues() {53 protected override List<List<double>> GenerateValues() { 54 54 List<List<double>> data = new List<List<double>>(); 55 55 for (int i = 0; i < AllowedInputVariables.Count(); i++) { … … 65 65 data.Add(results); 66 66 67 return ValueGenerator.Transformation(data);67 return data; 68 68 } 69 69 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Korns/KornsFunctionFive.cs
r7664 r7682 45 45 } 46 46 protected override string TargetVariable { get { return "Y"; } } 47 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X0", "X1", "X2", "X3", "X4", "Y" }; } }48 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X0", "X1", "X2", "X3", "X4" }; } }47 protected override string[] InputVariables { get { return new string[] { "X0", "X1", "X2", "X3", "X4", "Y" }; } } 48 protected override string[] AllowedInputVariables { get { return new string[] { "X0", "X1", "X2", "X3", "X4" }; } } 49 49 protected override int TrainingPartitionStart { get { return 0; } } 50 50 protected override int TrainingPartitionEnd { get { return 5000; } } … … 52 52 protected override int TestPartitionEnd { get { return 10000; } } 53 53 54 protected override double[,]GenerateValues() {54 protected override List<List<double>> GenerateValues() { 55 55 List<List<double>> data = new List<List<double>>(); 56 56 for (int i = 0; i < AllowedInputVariables.Count(); i++) { … … 66 66 data.Add(results); 67 67 68 return ValueGenerator.Transformation(data);68 return data; 69 69 } 70 70 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Korns/KornsFunctionFiveteen.cs
r7664 r7682 45 45 } 46 46 protected override string TargetVariable { get { return "Y"; } } 47 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X0", "X1", "X2", "X3", "X4", "Y" }; } }48 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X0", "X1", "X2", "X3", "X4" }; } }47 protected override string[] InputVariables { get { return new string[] { "X0", "X1", "X2", "X3", "X4", "Y" }; } } 48 protected override string[] AllowedInputVariables { get { return new string[] { "X0", "X1", "X2", "X3", "X4" }; } } 49 49 protected override int TrainingPartitionStart { get { return 0; } } 50 50 protected override int TrainingPartitionEnd { get { return 5000; } } … … 52 52 protected override int TestPartitionEnd { get { return 10000; } } 53 53 54 protected override double[,]GenerateValues() {54 protected override List<List<double>> GenerateValues() { 55 55 List<List<double>> data = new List<List<double>>(); 56 56 for (int i = 0; i < AllowedInputVariables.Count(); i++) { … … 69 69 data.Add(results); 70 70 71 return ValueGenerator.Transformation(data);71 return data; 72 72 } 73 73 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Korns/KornsFunctionFour.cs
r7664 r7682 44 44 } 45 45 protected override string TargetVariable { get { return "Y"; } } 46 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X0", "X1", "X2", "X3", "X4", "Y" }; } }47 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X0", "X1", "X2", "X3", "X4" }; } }46 protected override string[] InputVariables { get { return new string[] { "X0", "X1", "X2", "X3", "X4", "Y" }; } } 47 protected override string[] AllowedInputVariables { get { return new string[] { "X0", "X1", "X2", "X3", "X4" }; } } 48 48 protected override int TrainingPartitionStart { get { return 0; } } 49 49 protected override int TrainingPartitionEnd { get { return 5000; } } … … 51 51 protected override int TestPartitionEnd { get { return 10000; } } 52 52 53 protected override double[,]GenerateValues() {53 protected override List<List<double>> GenerateValues() { 54 54 List<List<double>> data = new List<List<double>>(); 55 55 for (int i = 0; i < AllowedInputVariables.Count(); i++) { … … 65 65 data.Add(results); 66 66 67 return ValueGenerator.Transformation(data);67 return data; 68 68 } 69 69 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Korns/KornsFunctionFourteen.cs
r7664 r7682 44 44 } 45 45 protected override string TargetVariable { get { return "Y"; } } 46 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X0", "X1", "X2", "X3", "X4", "Y" }; } }47 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X0", "X1", "X2", "X3", "X4" }; } }46 protected override string[] InputVariables { get { return new string[] { "X0", "X1", "X2", "X3", "X4", "Y" }; } } 47 protected override string[] AllowedInputVariables { get { return new string[] { "X0", "X1", "X2", "X3", "X4" }; } } 48 48 protected override int TrainingPartitionStart { get { return 0; } } 49 49 protected override int TrainingPartitionEnd { get { return 5000; } } … … 51 51 protected override int TestPartitionEnd { get { return 10000; } } 52 52 53 protected override double[,]GenerateValues() {53 protected override List<List<double>> GenerateValues() { 54 54 List<List<double>> data = new List<List<double>>(); 55 55 for (int i = 0; i < AllowedInputVariables.Count(); i++) { … … 68 68 data.Add(results); 69 69 70 return ValueGenerator.Transformation(data);70 return data; 71 71 } 72 72 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Korns/KornsFunctionNine.cs
r7664 r7682 45 45 } 46 46 protected override string TargetVariable { get { return "Y"; } } 47 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X0", "X1", "X2", "X3", "X4", "Y" }; } }48 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X0", "X1", "X2", "X3", "X4" }; } }47 protected override string[] InputVariables { get { return new string[] { "X0", "X1", "X2", "X3", "X4", "Y" }; } } 48 protected override string[] AllowedInputVariables { get { return new string[] { "X0", "X1", "X2", "X3", "X4" }; } } 49 49 protected override int TrainingPartitionStart { get { return 0; } } 50 50 protected override int TrainingPartitionEnd { get { return 5000; } } … … 52 52 protected override int TestPartitionEnd { get { return 10000; } } 53 53 54 protected override double[,]GenerateValues() {54 protected override List<List<double>> GenerateValues() { 55 55 List<List<double>> data = new List<List<double>>(); 56 56 for (int i = 0; i < AllowedInputVariables.Count(); i++) { … … 69 69 data.Add(results); 70 70 71 return ValueGenerator.Transformation(data);71 return data; 72 72 } 73 73 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Korns/KornsFunctionOne.cs
r7664 r7682 44 44 } 45 45 protected override string TargetVariable { get { return "Y"; } } 46 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X0", "X1", "X2", "X3", "X4", "Y" }; } }47 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X0", "X1", "X2", "X3", "X4" }; } }46 protected override string[] InputVariables { get { return new string[] { "X0", "X1", "X2", "X3", "X4", "Y" }; } } 47 protected override string[] AllowedInputVariables { get { return new string[] { "X0", "X1", "X2", "X3", "X4" }; } } 48 48 protected override int TrainingPartitionStart { get { return 0; } } 49 49 protected override int TrainingPartitionEnd { get { return 5000; } } … … 51 51 protected override int TestPartitionEnd { get { return 10000; } } 52 52 53 protected override double[,]GenerateValues() {53 protected override List<List<double>> GenerateValues() { 54 54 List<List<double>> data = new List<List<double>>(); 55 55 for (int i = 0; i < AllowedInputVariables.Count(); i++) { … … 65 65 data.Add(results); 66 66 67 return ValueGenerator.Transformation(data);67 return data; 68 68 } 69 69 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Korns/KornsFunctionSeven.cs
r7664 r7682 44 44 } 45 45 protected override string TargetVariable { get { return "Y"; } } 46 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X0", "X1", "X2", "X3", "X4", "Y" }; } }47 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X0", "X1", "X2", "X3", "X4" }; } }46 protected override string[] InputVariables { get { return new string[] { "X0", "X1", "X2", "X3", "X4", "Y" }; } } 47 protected override string[] AllowedInputVariables { get { return new string[] { "X0", "X1", "X2", "X3", "X4" }; } } 48 48 protected override int TrainingPartitionStart { get { return 0; } } 49 49 protected override int TrainingPartitionEnd { get { return 5000; } } … … 51 51 protected override int TestPartitionEnd { get { return 10000; } } 52 52 53 protected override double[,]GenerateValues() {53 protected override List<List<double>> GenerateValues() { 54 54 List<List<double>> data = new List<List<double>>(); 55 55 for (int i = 0; i < AllowedInputVariables.Count(); i++) { … … 65 65 data.Add(results); 66 66 67 return ValueGenerator.Transformation(data);67 return data; 68 68 } 69 69 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Korns/KornsFunctionSix.cs
r7664 r7682 45 45 } 46 46 protected override string TargetVariable { get { return "Y"; } } 47 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X0", "X1", "X2", "X3", "X4", "Y" }; } }48 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X0", "X1", "X2", "X3", "X4" }; } }47 protected override string[] InputVariables { get { return new string[] { "X0", "X1", "X2", "X3", "X4", "Y" }; } } 48 protected override string[] AllowedInputVariables { get { return new string[] { "X0", "X1", "X2", "X3", "X4" }; } } 49 49 protected override int TrainingPartitionStart { get { return 0; } } 50 50 protected override int TrainingPartitionEnd { get { return 5000; } } … … 52 52 protected override int TestPartitionEnd { get { return 10000; } } 53 53 54 protected override double[,]GenerateValues() {54 protected override List<List<double>> GenerateValues() { 55 55 List<List<double>> data = new List<List<double>>(); 56 56 for (int i = 0; i < AllowedInputVariables.Count(); i++) { … … 66 66 data.Add(results); 67 67 68 return ValueGenerator.Transformation(data);68 return data; 69 69 } 70 70 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Korns/KornsFunctionTen.cs
r7664 r7682 44 44 } 45 45 protected override string TargetVariable { get { return "Y"; } } 46 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X0", "X1", "X2", "X3", "X4", "Y" }; } }47 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X0", "X1", "X2", "X3", "X4" }; } }46 protected override string[] InputVariables { get { return new string[] { "X0", "X1", "X2", "X3", "X4", "Y" }; } } 47 protected override string[] AllowedInputVariables { get { return new string[] { "X0", "X1", "X2", "X3", "X4" }; } } 48 48 protected override int TrainingPartitionStart { get { return 0; } } 49 49 protected override int TrainingPartitionEnd { get { return 5000; } } … … 51 51 protected override int TestPartitionEnd { get { return 10000; } } 52 52 53 protected override double[,]GenerateValues() {53 protected override List<List<double>> GenerateValues() { 54 54 List<List<double>> data = new List<List<double>>(); 55 55 for (int i = 0; i < AllowedInputVariables.Count(); i++) { … … 68 68 data.Add(results); 69 69 70 return ValueGenerator.Transformation(data);70 return data; 71 71 } 72 72 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Korns/KornsFunctionThirteen.cs
r7664 r7682 44 44 } 45 45 protected override string TargetVariable { get { return "Y"; } } 46 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X0", "X1", "X2", "X3", "X4", "Y" }; } }47 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X0", "X1", "X2", "X3", "X4" }; } }46 protected override string[] InputVariables { get { return new string[] { "X0", "X1", "X2", "X3", "X4", "Y" }; } } 47 protected override string[] AllowedInputVariables { get { return new string[] { "X0", "X1", "X2", "X3", "X4" }; } } 48 48 protected override int TrainingPartitionStart { get { return 0; } } 49 49 protected override int TrainingPartitionEnd { get { return 5000; } } … … 51 51 protected override int TestPartitionEnd { get { return 10000; } } 52 52 53 protected override double[,]GenerateValues() {53 protected override List<List<double>> GenerateValues() { 54 54 List<List<double>> data = new List<List<double>>(); 55 55 for (int i = 0; i < AllowedInputVariables.Count(); i++) { … … 68 68 data.Add(results); 69 69 70 return ValueGenerator.Transformation(data);70 return data; 71 71 } 72 72 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Korns/KornsFunctionThree.cs
r7664 r7682 44 44 } 45 45 protected override string TargetVariable { get { return "Y"; } } 46 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X0", "X1", "X2", "X3", "X4", "Y" }; } }47 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X0", "X1", "X2", "X3", "X4" }; } }46 protected override string[] InputVariables { get { return new string[] { "X0", "X1", "X2", "X3", "X4", "Y" }; } } 47 protected override string[] AllowedInputVariables { get { return new string[] { "X0", "X1", "X2", "X3", "X4" }; } } 48 48 protected override int TrainingPartitionStart { get { return 0; } } 49 49 protected override int TrainingPartitionEnd { get { return 5000; } } … … 51 51 protected override int TestPartitionEnd { get { return 10000; } } 52 52 53 protected override double[,]GenerateValues() {53 protected override List<List<double>> GenerateValues() { 54 54 List<List<double>> data = new List<List<double>>(); 55 55 for (int i = 0; i < AllowedInputVariables.Count(); i++) { … … 68 68 data.Add(results); 69 69 70 return ValueGenerator.Transformation(data);70 return data; 71 71 } 72 72 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Korns/KornsFunctionTwelve.cs
r7664 r7682 44 44 } 45 45 protected override string TargetVariable { get { return "Y"; } } 46 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X0", "X1", "X2", "X3", "X4", "Y" }; } }47 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X0", "X1", "X2", "X3", "X4" }; } }46 protected override string[] InputVariables { get { return new string[] { "X0", "X1", "X2", "X3", "X4", "Y" }; } } 47 protected override string[] AllowedInputVariables { get { return new string[] { "X0", "X1", "X2", "X3", "X4" }; } } 48 48 protected override int TrainingPartitionStart { get { return 0; } } 49 49 protected override int TrainingPartitionEnd { get { return 5000; } } … … 51 51 protected override int TestPartitionEnd { get { return 10000; } } 52 52 53 protected override double[,]GenerateValues() {53 protected override List<List<double>> GenerateValues() { 54 54 List<List<double>> data = new List<List<double>>(); 55 55 for (int i = 0; i < AllowedInputVariables.Count(); i++) { … … 66 66 data.Add(results); 67 67 68 return ValueGenerator.Transformation(data);68 return data; 69 69 } 70 70 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Korns/KornsFunctionTwo.cs
r7664 r7682 44 44 } 45 45 protected override string TargetVariable { get { return "Y"; } } 46 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X0", "X1", "X2", "X3", "X4", "Y" }; } }47 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X0", "X1", "X2", "X3", "X4" }; } }46 protected override string[] InputVariables { get { return new string[] { "X0", "X1", "X2", "X3", "X4", "Y" }; } } 47 protected override string[] AllowedInputVariables { get { return new string[] { "X0", "X1", "X2", "X3", "X4" }; } } 48 48 protected override int TrainingPartitionStart { get { return 0; } } 49 49 protected override int TrainingPartitionEnd { get { return 5000; } } … … 51 51 protected override int TestPartitionEnd { get { return 10000; } } 52 52 53 protected override double[,]GenerateValues() {53 protected override List<List<double>> GenerateValues() { 54 54 List<List<double>> data = new List<List<double>>(); 55 55 for (int i = 0; i < AllowedInputVariables.Count(); i++) { … … 67 67 data.Add(results); 68 68 69 return ValueGenerator.Transformation(data);69 return data; 70 70 } 71 71 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Nguyen/NguyenFunctionEight.cs
r7664 r7682 38 38 } 39 39 protected override string TargetVariable { get { return "Y"; } } 40 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X", "Y" }; } }41 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X" }; } }40 protected override string[] InputVariables { get { return new string[] { "X", "Y" }; } } 41 protected override string[] AllowedInputVariables { get { return new string[] { "X" }; } } 42 42 protected override int TrainingPartitionStart { get { return 0; } } 43 43 protected override int TrainingPartitionEnd { get { return 20; } } … … 45 45 protected override int TestPartitionEnd { get { return 350; } } 46 46 47 protected override double[,]GenerateValues() {47 protected override List<List<double>> GenerateValues() { 48 48 List<List<double>> data = new List<List<double>>(); 49 49 data.Add(ValueGenerator.GenerateUniformDistributedValues(500, 0, 4)); … … 57 57 data.Add(results); 58 58 59 return ValueGenerator.Transformation(data);59 return data; 60 60 } 61 61 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Nguyen/NguyenFunctionEleven.cs
r7664 r7682 38 38 } 39 39 protected override string TargetVariable { get { return "Z"; } } 40 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X", "Y", "Z" }; } }41 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X", "Y" }; } }40 protected override string[] InputVariables { get { return new string[] { "X", "Y", "Z" }; } } 41 protected override string[] AllowedInputVariables { get { return new string[] { "X", "Y" }; } } 42 42 protected override int TrainingPartitionStart { get { return 0; } } 43 43 protected override int TrainingPartitionEnd { get { return 100; } } … … 45 45 protected override int TestPartitionEnd { get { return 1000; } } 46 46 47 protected override double[,]GenerateValues() {47 protected override List<List<double>> GenerateValues() { 48 48 List<List<double>> data = new List<List<double>>(); 49 49 data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, 0, 1)); … … 59 59 data.Add(results); 60 60 61 return ValueGenerator.Transformation(data);61 return data; 62 62 } 63 63 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Nguyen/NguyenFunctionFive.cs
r7664 r7682 38 38 } 39 39 protected override string TargetVariable { get { return "Y"; } } 40 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X", "Y" }; } }41 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X" }; } }40 protected override string[] InputVariables { get { return new string[] { "X", "Y" }; } } 41 protected override string[] AllowedInputVariables { get { return new string[] { "X" }; } } 42 42 protected override int TrainingPartitionStart { get { return 0; } } 43 43 protected override int TrainingPartitionEnd { get { return 20; } } … … 45 45 protected override int TestPartitionEnd { get { return 350; } } 46 46 47 protected override double[,]GenerateValues() {47 protected override List<List<double>> GenerateValues() { 48 48 List<List<double>> data = new List<List<double>>(); 49 49 data.Add(ValueGenerator.GenerateUniformDistributedValues(500, -1, 1)); … … 57 57 data.Add(results); 58 58 59 return ValueGenerator.Transformation(data);59 return data; 60 60 } 61 61 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Nguyen/NguyenFunctionFour.cs
r7664 r7682 38 38 } 39 39 protected override string TargetVariable { get { return "Y"; } } 40 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X", "Y" }; } }41 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X" }; } }40 protected override string[] InputVariables { get { return new string[] { "X", "Y" }; } } 41 protected override string[] AllowedInputVariables { get { return new string[] { "X" }; } } 42 42 protected override int TrainingPartitionStart { get { return 0; } } 43 43 protected override int TrainingPartitionEnd { get { return 20; } } … … 45 45 protected override int TestPartitionEnd { get { return 350; } } 46 46 47 protected override double[,]GenerateValues() {47 protected override List<List<double>> GenerateValues() { 48 48 List<List<double>> data = new List<List<double>>(); 49 49 data.Add(ValueGenerator.GenerateUniformDistributedValues(500, -1, 1)); … … 57 57 data.Add(results); 58 58 59 return ValueGenerator.Transformation(data);59 return data; 60 60 } 61 61 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Nguyen/NguyenFunctionNine.cs
r7664 r7682 38 38 } 39 39 protected override string TargetVariable { get { return "Z"; } } 40 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X", "Y", "Z" }; } }41 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X", "Y" }; } }40 protected override string[] InputVariables { get { return new string[] { "X", "Y", "Z" }; } } 41 protected override string[] AllowedInputVariables { get { return new string[] { "X", "Y" }; } } 42 42 protected override int TrainingPartitionStart { get { return 0; } } 43 43 protected override int TrainingPartitionEnd { get { return 100; } } … … 45 45 protected override int TestPartitionEnd { get { return 1000; } } 46 46 47 protected override double[,]GenerateValues() {47 protected override List<List<double>> GenerateValues() { 48 48 List<List<double>> data = new List<List<double>>(); 49 49 data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, 0, 1)); … … 59 59 data.Add(results); 60 60 61 return ValueGenerator.Transformation(data);61 return data; 62 62 } 63 63 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Nguyen/NguyenFunctionOne.cs
r7664 r7682 38 38 } 39 39 protected override string TargetVariable { get { return "Y"; } } 40 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X", "Y" }; } }41 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X" }; } }40 protected override string[] InputVariables { get { return new string[] { "X", "Y" }; } } 41 protected override string[] AllowedInputVariables { get { return new string[] { "X" }; } } 42 42 protected override int TrainingPartitionStart { get { return 0; } } 43 43 protected override int TrainingPartitionEnd { get { return 20; } } … … 45 45 protected override int TestPartitionEnd { get { return 350; } } 46 46 47 protected override double[,]GenerateValues() {47 protected override List<List<double>> GenerateValues() { 48 48 List<List<double>> data = new List<List<double>>(); 49 49 data.Add(ValueGenerator.GenerateUniformDistributedValues(500, -1, 1)); … … 57 57 data.Add(results); 58 58 59 return ValueGenerator.Transformation(data);59 return data; 60 60 } 61 61 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Nguyen/NguyenFunctionSeven.cs
r7664 r7682 38 38 } 39 39 protected override string TargetVariable { get { return "Y"; } } 40 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X", "Y" }; } }41 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X" }; } }40 protected override string[] InputVariables { get { return new string[] { "X", "Y" }; } } 41 protected override string[] AllowedInputVariables { get { return new string[] { "X" }; } } 42 42 protected override int TrainingPartitionStart { get { return 0; } } 43 43 protected override int TrainingPartitionEnd { get { return 20; } } … … 45 45 protected override int TestPartitionEnd { get { return 350; } } 46 46 47 protected override double[,]GenerateValues() {47 protected override List<List<double>> GenerateValues() { 48 48 List<List<double>> data = new List<List<double>>(); 49 49 data.Add(ValueGenerator.GenerateUniformDistributedValues(500, 0, 2)); … … 57 57 data.Add(results); 58 58 59 return ValueGenerator.Transformation(data);59 return data; 60 60 } 61 61 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Nguyen/NguyenFunctionSix.cs
r7664 r7682 38 38 } 39 39 protected override string TargetVariable { get { return "Y"; } } 40 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X", "Y" }; } }41 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X" }; } }40 protected override string[] InputVariables { get { return new string[] { "X", "Y" }; } } 41 protected override string[] AllowedInputVariables { get { return new string[] { "X" }; } } 42 42 protected override int TrainingPartitionStart { get { return 0; } } 43 43 protected override int TrainingPartitionEnd { get { return 20; } } … … 45 45 protected override int TestPartitionEnd { get { return 350; } } 46 46 47 protected override double[,]GenerateValues() {47 protected override List<List<double>> GenerateValues() { 48 48 List<List<double>> data = new List<List<double>>(); 49 49 data.Add(ValueGenerator.GenerateUniformDistributedValues(500, -1, 1)); … … 57 57 data.Add(results); 58 58 59 return ValueGenerator.Transformation(data);59 return data; 60 60 } 61 61 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Nguyen/NguyenFunctionTen.cs
r7664 r7682 38 38 } 39 39 protected override string TargetVariable { get { return "Z"; } } 40 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X", "Y", "Z" }; } }41 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X", "Y" }; } }40 protected override string[] InputVariables { get { return new string[] { "X", "Y", "Z" }; } } 41 protected override string[] AllowedInputVariables { get { return new string[] { "X", "Y" }; } } 42 42 protected override int TrainingPartitionStart { get { return 0; } } 43 43 protected override int TrainingPartitionEnd { get { return 100; } } … … 45 45 protected override int TestPartitionEnd { get { return 1000; } } 46 46 47 protected override double[,]GenerateValues() {47 protected override List<List<double>> GenerateValues() { 48 48 List<List<double>> data = new List<List<double>>(); 49 49 data.Add(ValueGenerator.GenerateUniformDistributedValues(1000, 0, 1)); … … 59 59 data.Add(results); 60 60 61 return ValueGenerator.Transformation(data);61 return data; 62 62 } 63 63 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Nguyen/NguyenFunctionThree.cs
r7664 r7682 38 38 } 39 39 protected override string TargetVariable { get { return "Y"; } } 40 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X", "Y" }; } }41 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X" }; } }40 protected override string[] InputVariables { get { return new string[] { "X", "Y" }; } } 41 protected override string[] AllowedInputVariables { get { return new string[] { "X" }; } } 42 42 protected override int TrainingPartitionStart { get { return 0; } } 43 43 protected override int TrainingPartitionEnd { get { return 20; } } … … 45 45 protected override int TestPartitionEnd { get { return 350; } } 46 46 47 protected override double[,]GenerateValues() {47 protected override List<List<double>> GenerateValues() { 48 48 List<List<double>> data = new List<List<double>>(); 49 49 data.Add(ValueGenerator.GenerateUniformDistributedValues(500, -1, 1)); … … 57 57 data.Add(results); 58 58 59 return ValueGenerator.Transformation(data);59 return data; 60 60 } 61 61 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Nguyen/NguyenFunctionTwelve.cs
r7664 r7682 38 38 } 39 39 protected override string TargetVariable { get { return "Z"; } } 40 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X", "Y", "Z" }; } }41 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X", "Y" }; } }40 protected override string[] InputVariables { get { return new string[] { "X", "Y", "Z" }; } } 41 protected override string[] AllowedInputVariables { get { return new string[] { "X", "Y" }; } } 42 42 protected override int TrainingPartitionStart { get { return 0; } } 43 43 protected override int TrainingPartitionEnd { get { return 100; } } … … 45 45 protected override int TestPartitionEnd { get { return 1000; } } 46 46 47 protected override double[,]GenerateValues() {47 protected override List<List<double>> GenerateValues() { 48 48 List<List<double>> data = new List<List<double>>(); 49 49 data.Add(ValueGenerator.GenerateUniformDistributedValues(1000, 0, 1)); … … 59 59 data.Add(results); 60 60 61 return ValueGenerator.Transformation(data);61 return data; 62 62 } 63 63 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Nguyen/NguyenFunctionTwo.cs
r7664 r7682 38 38 } 39 39 protected override string TargetVariable { get { return "Y"; } } 40 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X", "Y" }; } }41 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X" }; } }40 protected override string[] InputVariables { get { return new string[] { "X", "Y" }; } } 41 protected override string[] AllowedInputVariables { get { return new string[] { "X" }; } } 42 42 protected override int TrainingPartitionStart { get { return 0; } } 43 43 protected override int TrainingPartitionEnd { get { return 20; } } … … 45 45 protected override int TestPartitionEnd { get { return 350; } } 46 46 47 protected override double[,]GenerateValues() {47 protected override List<List<double>> GenerateValues() { 48 48 List<List<double>> data = new List<List<double>>(); 49 49 data.Add(ValueGenerator.GenerateUniformDistributedValues(500, -1, 1)); … … 57 57 data.Add(results); 58 58 59 return ValueGenerator.Transformation(data);59 return data; 60 60 } 61 61 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Properties/AssemblyInfo.cs
r7667 r7682 55 55 // [assembly: AssemblyVersion("1.0.*")] 56 56 [assembly: AssemblyVersion("3.4.0.0")] 57 [assembly: AssemblyFileVersion("3.4.0.766 6")]57 [assembly: AssemblyFileVersion("3.4.0.7667")] -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/RegressionInstanceProvider.cs
r7664 r7682 41 41 regData.Name = path.Substring(pos, path.Length - pos); 42 42 } 43 regData.InputVariables = new List<string>(csvFileParser.VariableNames) ;43 regData.InputVariables = new List<string>(csvFileParser.VariableNames).ToArray(); 44 44 regData.TargetVariable = csvFileParser.VariableNames.Last(); 45 regData.AllowedInputVariables = regData.InputVariables.Where(x => !x.Equals(regData.TargetVariable)) ;45 regData.AllowedInputVariables = regData.InputVariables.Where(x => !x.Equals(regData.TargetVariable)).ToArray(); 46 46 //convert to multidimensional array 47 47 List<IList> values = csvFileParser.Values; -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/TrentMcConaghy/TrentMcConaghyInstanceProvider.cs
r7667 r7682 49 49 50 50 regData.TargetVariable = regData.InputVariables.First(); 51 regData.AllowedInputVariables = regData.InputVariables.Where(x => !x.Equals(regData.TargetVariable)) ;51 regData.AllowedInputVariables = regData.InputVariables.Where(x => !x.Equals(regData.TargetVariable)).ToArray(); 52 52 53 53 return regData; -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/ValueGenerator.cs
r7664 r7682 28 28 public class ValueGenerator { 29 29 protected static FastRandom rand = new FastRandom(); 30 31 public static double[,] Transformation(List<List<double>> data) {32 if (!data.All(x => x.Count.Equals(data.First().Count)))33 throw new ArgumentException("Can't create jagged array.");34 double[,] values = new double[data.First().Count, data.Count];35 for (int i = 0; i < values.GetLength(0); i++) {36 for (int j = 0; j < values.GetLength(1); j++) {37 values[i, j] = data[j][i];38 }39 }40 return values;41 }42 30 43 31 public static List<double> GenerateSteps(double start, double end, double stepWidth) { -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Various/BreimanOne.cs
r7666 r7682 36 36 } 37 37 protected override string TargetVariable { get { return "Y"; } } 38 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X1", "X2", "X3", "X4", "X5", "X6", "X7", "X8", "X9", "X10", "Y" }; } }39 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X1", "X2", "X3", "X4", "X5", "X6", "X7", "X8", "X9", "X10" }; } }38 protected override string[] InputVariables { get { return new string[] { "X1", "X2", "X3", "X4", "X5", "X6", "X7", "X8", "X9", "X10", "Y" }; } } 39 protected override string[] AllowedInputVariables { get { return new string[] { "X1", "X2", "X3", "X4", "X5", "X6", "X7", "X8", "X9", "X10" }; } } 40 40 protected override int TrainingPartitionStart { get { return 0; } } 41 41 protected override int TrainingPartitionEnd { get { return 5001; } } … … 45 45 protected static FastRandom rand = new FastRandom(); 46 46 47 protected override double[,]GenerateValues() {47 protected override List<List<double>> GenerateValues() { 48 48 List<List<double>> data = new List<List<double>>(); 49 49 List<int> values = new List<int>() { -1, 1 }; … … 76 76 data.Add(results); 77 77 78 return ValueGenerator.Transformation(data);78 return data; 79 79 } 80 80 -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Various/PolyTen.cs
r7666 r7682 39 39 } 40 40 protected override string TargetVariable { get { return "Y"; } } 41 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X1", "X2", "X3", "X4", "X5", "X6", "X7", "X8", "X9", "X10", "Y" }; } }42 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X1", "X2", "X3", "X4", "X5", "X6", "X7", "X8", "X9", "X10" }; } }41 protected override string[] InputVariables { get { return new string[] { "X1", "X2", "X3", "X4", "X5", "X6", "X7", "X8", "X9", "X10", "Y" }; } } 42 protected override string[] AllowedInputVariables { get { return new string[] { "X1", "X2", "X3", "X4", "X5", "X6", "X7", "X8", "X9", "X10" }; } } 43 43 protected override int TrainingPartitionStart { get { return 0; } } 44 44 protected override int TrainingPartitionEnd { get { return 250; } } … … 46 46 protected override int TestPartitionEnd { get { return 500; } } 47 47 48 protected override double[,]GenerateValues() {48 protected override List<List<double>> GenerateValues() { 49 49 List<List<double>> data = new List<List<double>>(); 50 50 for (int i = 0; i < AllowedInputVariables.Count(); i++) { … … 69 69 data.Add(results); 70 70 71 return ValueGenerator.Transformation(data);71 return data; 72 72 } 73 73 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Various/SpatialCoevolution.cs
r7666 r7682 42 42 } 43 43 protected override string TargetVariable { get { return "F"; } } 44 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X", "Y", "F" }; } }45 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X", "Y" }; } }44 protected override string[] InputVariables { get { return new string[] { "X", "Y", "F" }; } } 45 protected override string[] AllowedInputVariables { get { return new string[] { "X", "Y" }; } } 46 46 protected override int TrainingPartitionStart { get { return 0; } } 47 47 protected override int TrainingPartitionEnd { get { return 250; } } … … 49 49 protected override int TestPartitionEnd { get { return 500; } } 50 50 51 protected override double[,]GenerateValues() {51 protected override List<List<double>> GenerateValues() { 52 52 List<List<double>> data = new List<List<double>>(); 53 53 … … 70 70 data.Add(results); 71 71 72 return ValueGenerator.Transformation(data);72 return data; 73 73 } 74 74 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Vladislavleva/KotanchekFunction.cs
r7666 r7682 39 39 } 40 40 protected override string TargetVariable { get { return "Y"; } } 41 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X1", "X2", "Y" }; } }42 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X1", "X2" }; } }41 protected override string[] InputVariables { get { return new string[] { "X1", "X2", "Y" }; } } 42 protected override string[] AllowedInputVariables { get { return new string[] { "X1", "X2" }; } } 43 43 protected override int TrainingPartitionStart { get { return 0; } } 44 44 protected override int TrainingPartitionEnd { get { return 100; } } … … 46 46 protected override int TestPartitionEnd { get { return 3025; } } 47 47 48 protected override double[,]GenerateValues() {48 protected override List<List<double>> GenerateValues() { 49 49 List<List<double>> data = new List<List<double>>(); 50 50 … … 66 66 data.Add(results); 67 67 68 return ValueGenerator.Transformation(data);68 return data; 69 69 } 70 70 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Vladislavleva/RationalPolynomialThreeDimensional.cs
r7664 r7682 39 39 } 40 40 protected override string TargetVariable { get { return "Y"; } } 41 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X1", "X2", "X3", "Y" }; } }42 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X1", "X2", "X3" }; } }41 protected override string[] InputVariables { get { return new string[] { "X1", "X2", "X3", "Y" }; } } 42 protected override string[] AllowedInputVariables { get { return new string[] { "X1", "X2", "X3" }; } } 43 43 protected override int TrainingPartitionStart { get { return 0; } } 44 44 protected override int TrainingPartitionEnd { get { return 300; } } … … 46 46 protected override int TestPartitionEnd { get { return 3700; } } 47 47 48 protected override double[,]GenerateValues() {48 protected override List<List<double>> GenerateValues() { 49 49 List<List<double>> data = new List<List<double>>(); 50 50 … … 76 76 data.Add(results); 77 77 78 return ValueGenerator.Transformation(data);78 return data; 79 79 } 80 80 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Vladislavleva/RationalPolynomialTwoDimensional.cs
r7664 r7682 39 39 } 40 40 protected override string TargetVariable { get { return "Y"; } } 41 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X1", "X2", "Y" }; } }42 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X1", "X2" }; } }41 protected override string[] InputVariables { get { return new string[] { "X1", "X2", "Y" }; } } 42 protected override string[] AllowedInputVariables { get { return new string[] { "X1", "X2" }; } } 43 43 protected override int TrainingPartitionStart { get { return 0; } } 44 44 protected override int TrainingPartitionEnd { get { return 50; } } … … 46 46 protected override int TestPartitionEnd { get { return 2157; } } 47 47 48 protected override double[,]GenerateValues() {48 protected override List<List<double>> GenerateValues() { 49 49 List<List<double>> data = new List<List<double>>(); 50 50 … … 67 67 data.Add(results); 68 68 69 return ValueGenerator.Transformation(data);69 return data; 70 70 } 71 71 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Vladislavleva/RippleFunction.cs
r7664 r7682 39 39 } 40 40 protected override string TargetVariable { get { return "Y"; } } 41 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X1", "X2", "Y" }; } }42 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X1", "X2" }; } }41 protected override string[] InputVariables { get { return new string[] { "X1", "X2", "Y" }; } } 42 protected override string[] AllowedInputVariables { get { return new string[] { "X1", "X2" }; } } 43 43 protected override int TrainingPartitionStart { get { return 0; } } 44 44 protected override int TrainingPartitionEnd { get { return 300; } } … … 46 46 protected override int TestPartitionEnd { get { return 1300; } } 47 47 48 protected override double[,]GenerateValues() {48 protected override List<List<double>> GenerateValues() { 49 49 List<List<double>> data = new List<List<double>>(); 50 50 for (int i = 0; i < AllowedInputVariables.Count(); i++) { … … 65 65 data.Add(results); 66 66 67 return ValueGenerator.Transformation(data);67 return data; 68 68 } 69 69 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Vladislavleva/SalutowiczFunctionOneDimensional.cs
r7664 r7682 38 38 } 39 39 protected override string TargetVariable { get { return "Y"; } } 40 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X", "Y" }; } }41 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X" }; } }40 protected override string[] InputVariables { get { return new string[] { "X", "Y" }; } } 41 protected override string[] AllowedInputVariables { get { return new string[] { "X" }; } } 42 42 protected override int TrainingPartitionStart { get { return 0; } } 43 43 protected override int TrainingPartitionEnd { get { return 100; } } … … 45 45 protected override int TestPartitionEnd { get { return 321; } } 46 46 47 protected override double[,]GenerateValues() {47 protected override List<List<double>> GenerateValues() { 48 48 List<List<double>> data = new List<List<double>>(); 49 49 data.Add(ValueGenerator.GenerateSteps(0.05, 10, 0.1)); … … 58 58 data.Add(results); 59 59 60 return ValueGenerator.Transformation(data);60 return data; 61 61 } 62 62 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Vladislavleva/SalutowiczFunctionTwoDimensional.cs
r7664 r7682 40 40 } 41 41 protected override string TargetVariable { get { return "Y"; } } 42 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X1", "X2", "Y" }; } }43 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X1", "X2" }; } }42 protected override string[] InputVariables { get { return new string[] { "X1", "X2", "Y" }; } } 43 protected override string[] AllowedInputVariables { get { return new string[] { "X1", "X2" }; } } 44 44 protected override int TrainingPartitionStart { get { return 0; } } 45 45 protected override int TrainingPartitionEnd { get { return 601; } } … … 47 47 protected override int TestPartitionEnd { get { return 3155; } } 48 48 49 protected override double[,]GenerateValues() {49 protected override List<List<double>> GenerateValues() { 50 50 List<List<double>> data = new List<List<double>>(); 51 51 List<List<double>> trainingData = new List<List<double>>() { … … 76 76 data.Add(results); 77 77 78 return ValueGenerator.Transformation(data);78 return data; 79 79 } 80 80 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Vladislavleva/SineCosineFunction.cs
r7664 r7682 39 39 } 40 40 protected override string TargetVariable { get { return "Y"; } } 41 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X1", "X2", "Y" }; } }42 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X1", "X2" }; } }41 protected override string[] InputVariables { get { return new string[] { "X1", "X2", "Y" }; } } 42 protected override string[] AllowedInputVariables { get { return new string[] { "X1", "X2" }; } } 43 43 protected override int TrainingPartitionStart { get { return 0; } } 44 44 protected override int TrainingPartitionEnd { get { return 30; } } … … 46 46 protected override int TestPartitionEnd { get { return 1461; } } 47 47 48 protected override double[,]GenerateValues() {48 protected override List<List<double>> GenerateValues() { 49 49 List<List<double>> data = new List<List<double>>(); 50 50 List<double> oneVariableTestData = ValueGenerator.GenerateSteps(-0.05, 6.05, 0.02); … … 66 66 data.Add(results); 67 67 68 return ValueGenerator.Transformation(data);68 return data; 69 69 } 70 70 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Regression/3.4/Vladislavleva/UnwrappedBallFunctionFiveDimensional.cs
r7664 r7682 39 39 } 40 40 protected override string TargetVariable { get { return "Y"; } } 41 protected override IEnumerable<string> InputVariables { get { return new List<string>(){ "X1", "X2", "X3", "X4", "X5", "Y" }; } }42 protected override IEnumerable<string> AllowedInputVariables { get { return new List<string>(){ "X1", "X2", "X3", "X4", "X5" }; } }41 protected override string[] InputVariables { get { return new string[] { "X1", "X2", "X3", "X4", "X5", "Y" }; } } 42 protected override string[] AllowedInputVariables { get { return new string[] { "X1", "X2", "X3", "X4", "X5" }; } } 43 43 protected override int TrainingPartitionStart { get { return 0; } } 44 44 protected override int TrainingPartitionEnd { get { return 1024; } } … … 46 46 protected override int TestPartitionEnd { get { return 6024; } } 47 47 48 protected override double[,]GenerateValues() {48 protected override List<List<double>> GenerateValues() { 49 49 List<List<double>> data = new List<List<double>>(); 50 50 for (int i = 0; i < AllowedInputVariables.Count(); i++) { … … 65 65 data.Add(results); 66 66 67 return ValueGenerator.Transformation(data);67 return data; 68 68 } 69 69 } -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Views/3.4/Plugin.cs
r7667 r7682 23 23 24 24 namespace HeuristicLab.Problems.Instances.Views { 25 [Plugin("HeuristicLab.Problems.Instances.Views", "3.4.0.766 6")]25 [Plugin("HeuristicLab.Problems.Instances.Views", "3.4.0.7667")] 26 26 [PluginFile("HeuristicLab.Problems.Instances.Views-3.4.dll", PluginFileType.Assembly)] 27 27 [PluginDependency("HeuristicLab.Common", "3.3")] -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances.Views/3.4/Properties/AssemblyInfo.cs
r7667 r7682 53 53 // by using the '*' as shown below: 54 54 [assembly: AssemblyVersion("3.4.0.0")] 55 [assembly: AssemblyFileVersion("3.4.2.766 6")]55 [assembly: AssemblyFileVersion("3.4.2.7667")] -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances/3.3/HeuristicLab.Problems.Instances-3.3.csproj
r7664 r7682 116 116 <Compile Include="IExportable.cs" /> 117 117 <Compile Include="TableFileParser.cs" /> 118 <Compile Include="Transformer.cs" /> 118 119 <Compile Include="Types\ATSPData.cs" /> 120 <Compile Include="Types\ClassificationData.cs" /> 119 121 <Compile Include="Types\RegressionData.cs" /> 120 122 <Compile Include="Types\CTAPData.cs" /> -
branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.Instances/3.3/Types/RegressionData.cs
r7603 r7682 20 20 #endregion 21 21 22 23 using System.Collections.Generic;24 22 namespace HeuristicLab.Problems.Instances { 25 23 … … 36 34 /// </summary> 37 35 public string Description { get; set; } 38 36 /// <summary> 37 /// The target variable of a problem. 38 /// </summary> 39 39 public string TargetVariable { get; set; } 40 41 public IEnumerable<string> InputVariables { get; set; } 42 43 public IEnumerable<string> AllowedInputVariables { get; set; } 44 40 /// <summary> 41 /// All variables which are in the problem. 42 /// </summary> 43 public string[] InputVariables { get; set; } 44 /// <summary> 45 /// All variables which shall be used to solve the problem. 46 /// (Variables wich are not contained by AllowedInputVariables won't be checked initialy, when the problem is created.) 47 /// </summary> 48 public string[] AllowedInputVariables { get; set; } 49 /// <summary> 50 /// Start of the trainings partition 51 /// </summary> 45 52 public int TrainingPartitionStart { get; set; } 53 /// <summary> 54 /// End of the trainings partition 55 /// </summary> 46 56 public int TrainingPartitionEnd { get; set; } 47 57 /// <summary> 58 /// Start of the test partition 59 /// </summary> 48 60 public int TestPartitionStart { get; set; } 61 /// <summary> 62 /// End of the test partition 63 /// </summary> 49 64 public int TestPartitionEnd { get; set; } 50 65 /// <summary> 66 /// Contains all the values of the variables 67 /// </summary> 51 68 public double[,] Values { get; set; } 52 69 }
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