- Timestamp:
- 07/05/12 18:10:08 (12 years ago)
- Location:
- trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Korns
- Files:
-
- 5 edited
Legend:
- Unmodified
- Added
- Removed
-
trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Korns/KornsFunctionEight.cs
r8225 r8245 53 53 protected override List<List<double>> GenerateValues() { 54 54 List<List<double>> data = new List<List<double>>(); 55 for (int i = 0; i < AllowedInputVariables.Count(); i++) { 56 data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, -50, 50).ToList()); 57 } 55 data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, 0, 50).ToList()); // note: range is only [0,50] to prevent NaN values (deviates from gp benchmark paper) 56 data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, -50, 50).ToList()); 57 data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, -50, 50).ToList()); 58 data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, 0, 50).ToList()); // note: range is only [0,50] to prevent NaN values (deviates from gp benchmark paper) 59 data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, 0, 50).ToList()); // note: range is only [0,50] to prevent NaN values (deviates from gp benchmark paper) 58 60 59 61 double x0, x3, x4; -
trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Korns/KornsFunctionFive.cs
r8225 r8245 53 53 protected override List<List<double>> GenerateValues() { 54 54 List<List<double>> data = new List<List<double>>(); 55 for (int i = 0; i < AllowedInputVariables.Count(); i++) { 56 data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, -50, 50).ToList()); 57 } 55 data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, -50, 50).ToList()); 56 data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, -50, 50).ToList()); 57 data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, -50, 50).ToList()); 58 data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, -50, 50).ToList()); 59 data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, 0, 50).ToList()); // note: range is only [0,50] to prevent NaN values (deviates from gp benchmark paper) 58 60 59 61 double x4; -
trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Korns/KornsFunctionFiveteen.cs
r8225 r8245 53 53 protected override List<List<double>> GenerateValues() { 54 54 List<List<double>> data = new List<List<double>>(); 55 for (int i = 0; i < AllowedInputVariables.Count(); i++) { 56 data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, 0, 50).ToList()); 57 } 55 data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, -50, 50).ToList()); 56 data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, -50, 50).ToList()); 57 data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, 0, 50).ToList()); // note: range is only [0,50] to prevent NaN values (deviates from gp benchmark paper) 58 data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, -50, 50).ToList()); 59 data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, -50, 50).ToList()); 58 60 59 61 double x0, x1, x2, x3; -
trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Korns/KornsFunctionNine.cs
r8225 r8245 53 53 protected override List<List<double>> GenerateValues() { 54 54 List<List<double>> data = new List<List<double>>(); 55 for (int i = 0; i < AllowedInputVariables.Count(); i++) { 56 data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, -50, 50).ToList()); 57 } 55 data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, 0, 50).ToList()); // note: range is only [0,50] to prevent NaN values (deviates from gp benchmark paper) 56 data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, 0, 50).ToList()); // note: range is only [0,50] to prevent NaN values (deviates from gp benchmark paper) 57 data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, -50, 50).ToList()); 58 data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, -50, 50).ToList()); 59 data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, -50, 50).ToList()); 58 60 59 61 double x0, x1, x2, x3; -
trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Korns/KornsFunctionSix.cs
r8225 r8245 53 53 protected override List<List<double>> GenerateValues() { 54 54 List<List<double>> data = new List<List<double>>(); 55 for (int i = 0; i < AllowedInputVariables.Count(); i++) { 56 data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, -50, 50).ToList()); 57 } 55 data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, 0, 50).ToList()); // note: range is only [0,50] to prevent NaN values (deviates from gp benchmark paper) 56 data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, -50, 50).ToList()); 57 data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, -50, 50).ToList()); 58 data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, -50, 50).ToList()); 59 data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, -50, 50).ToList()); 58 60 59 61 double x0;
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