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Changeset 8999 for trunk


Ignore:
Timestamp:
12/04/12 20:04:44 (12 years ago)
Author:
gkronber
Message:

#1979 adapted Vladislavleva instances to match the definition from the GP Benchmarks paper

Location:
trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Vladislavleva
Files:
6 edited

Legend:

Unmodified
Added
Removed

  • trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Vladislavleva/KotanchekFunction.cs

    r8825 r8999  
    3434        + "Function: F1(X1, X2) = exp(-(X1 - 1))² / (1.2 + (X2 -2.5)²" + Environment.NewLine
    3535        + "Training Data: 100 points X1, X2 = Rand(0.3, 4)" + Environment.NewLine
    36         + "Test Data: 2026 points (X1, X2) = (-0.2:0.1:4.2)" + Environment.NewLine
     36        + "Test Data: 441*441 points (X1, X2) = (-0.2:0.01:4.2)" + Environment.NewLine
    3737        + "Function Set: +, -, *, /, square, e^x, e^-x, x^eps, x + eps, x * eps";
    3838      }
    … …  
    4444    protected override int TrainingPartitionEnd { get { return 100; } }
    4545    protected override int TestPartitionStart { get { return 100; } }
    46     protected override int TestPartitionEnd { get { return 2126; } }
     46    protected override int TestPartitionEnd { get { return 100 + (441 * 441); } }
    4747
    4848    protected override List<List<double>> GenerateValues() {
    4949      List<List<double>> data = new List<List<double>>();
    5050
    51       List<double> oneVariableTestData = ValueGenerator.GenerateSteps(-0.2, 4.2, 0.1).ToList();
     51      List<double> oneVariableTestData = ValueGenerator.GenerateSteps(-0.2, 4.2, 0.01).ToList();
    5252      List<List<double>> testData = new List<List<double>>() { oneVariableTestData, oneVariableTestData };
    5353      var combinations = ValueGenerator.GenerateAllCombinationsOfValuesInLists(testData).ToList<IEnumerable<double>>();

  • trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Vladislavleva/RationalPolynomialThreeDimensional.cs

    r8825 r8999  
    3434        + "Function: F5(X1, X2, X3) = 30 * ((X1 - 1) * (X3 -1)) / (X2² * (X1 - 10))" + Environment.NewLine
    3535        + "Training Data: 300 points X1, X3 = Rand(0.05, 2), X2 = Rand(1, 2)" + Environment.NewLine
    36         + "Test Data: 2701 points X1, X3 = (-0.05:0.15:2.1), X2 = (0.95:0.1:2.05)" + Environment.NewLine
     36        + "Test Data: (14*12*14) points X1, X3 = (-0.05:0.15:2.1), X2 = (0.95:0.1:2.05)" + Environment.NewLine
    3737        + "Function Set: +, -, *, /, square, x^eps, x + eps, x * eps";
    3838      }
    … …  
    4343    protected override int TrainingPartitionStart { get { return 0; } }
    4444    protected override int TrainingPartitionEnd { get { return 300; } }
    45     protected override int TestPartitionStart { get { return 1000; } }
    46     protected override int TestPartitionEnd { get { return 3700; } }
     45    protected override int TestPartitionStart { get { return 300; } }
     46    protected override int TestPartitionEnd { get { return 300 + (14*12*14); } }
    4747
    4848    protected override List<List<double>> GenerateValues() {
    4949      List<List<double>> data = new List<List<double>>();
    5050
    51       int n = 1000;
     51      int n = 300;
    5252      data.Add(ValueGenerator.GenerateUniformDistributedValues(n, 0.05, 2).ToList());
    5353      data.Add(ValueGenerator.GenerateUniformDistributedValues(n, 1, 2).ToList());

  • trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Vladislavleva/RationalPolynomialTwoDimensional.cs

    r8825 r8999  
    3434        + "Function: F8(X1, X2) = ((X1 - 3)^4 + (X2 - 3)³ - (X2 -3)) / ((X2 - 2)^4 + 10)" + Environment.NewLine
    3535        + "Training Data: 50 points X1, X2 = Rand(0.05, 6.05)" + Environment.NewLine
    36         + "Test Data: 1157 points X1, X2 = (-0.25:0.2:6.35)" + Environment.NewLine
     36        + "Test Data: 34*34 points X1, X2 = (-0.25:0.2:6.35)" + Environment.NewLine
    3737        + "Function Set: +, -, *, /, square, x^eps, x + eps, x * eps";
    3838      }
    … …  
    4343    protected override int TrainingPartitionStart { get { return 0; } }
    4444    protected override int TrainingPartitionEnd { get { return 50; } }
    45     protected override int TestPartitionStart { get { return 1000; } }
    46     protected override int TestPartitionEnd { get { return 2157; } }
     45    protected override int TestPartitionStart { get { return 50; } }
     46    protected override int TestPartitionEnd { get { return 50 + (34 * 34); } }
    4747
    4848    protected override List<List<double>> GenerateValues() {
    … …  
    5050
    5151      List<double> oneVariableTestData = ValueGenerator.GenerateSteps(-0.25, 6.35, 0.2).ToList();
     52
    5253      List<List<double>> testData = new List<List<double>>() { oneVariableTestData, oneVariableTestData };
     54      var combinations = ValueGenerator.GenerateAllCombinationsOfValuesInLists(testData).ToList<IEnumerable<double>>();
    5355
    54       var combinations = ValueGenerator.GenerateAllCombinationsOfValuesInLists(testData).ToList<IEnumerable<double>>();
    5556      for (int i = 0; i < AllowedInputVariables.Count(); i++) {
    56         data.Add(ValueGenerator.GenerateUniformDistributedValues(1000, 0.05, 6.05).ToList());
     57        data.Add(ValueGenerator.GenerateUniformDistributedValues(50, 0.05, 6.05).ToList());
    5758        data[i].AddRange(combinations[i]);
    5859      }

  • trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Vladislavleva/RippleFunction.cs

    r8825 r8999  
    2727  public class RippleFunction : ArtificialRegressionDataDescriptor {
    2828
    29     public override string Name { get { return "Vladislavleva-7  F7(X1, X2) = (X1 - 3)(X2 - 3) + 2 * sin((X1 - 4)(X2 - 4))"; } }
     29    public override string Name { get { return "Vladislavleva-7 F7(X1, X2) = (X1 - 3)(X2 - 3) + 2 * sin((X1 - 4)(X2 - 4))"; } }
    3030    public override string Description {
    3131      get {
    … …  
    4444    protected override int TrainingPartitionEnd { get { return 300; } }
    4545    protected override int TestPartitionStart { get { return 300; } }
    46     protected override int TestPartitionEnd { get { return 1300; } }
     46    protected override int TestPartitionEnd { get { return 300 + 1000; } }
    4747
    4848    protected override List<List<double>> GenerateValues() {
    4949      List<List<double>> data = new List<List<double>>();
    5050      for (int i = 0; i < AllowedInputVariables.Count(); i++) {
    51         data.Add(ValueGenerator.GenerateUniformDistributedValues(TrainingPartitionEnd, 0.05, 6.05).ToList());
     51        data.Add(ValueGenerator.GenerateUniformDistributedValues(300, 0.05, 6.05).ToList());
    5252      }
    5353
    5454      for (int i = 0; i < AllowedInputVariables.Count(); i++) {
    55         data[i].AddRange(ValueGenerator.GenerateUniformDistributedValues(TrainingPartitionEnd, -0.25, 6.35));
     55        data[i].AddRange(ValueGenerator.GenerateUniformDistributedValues(1000, -0.25, 6.35));
    5656      }
    5757

  • trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Vladislavleva/SalutowiczFunctionTwoDimensional.cs

    r8825 r8999  
    3333        + "Authors: Ekaterina J. Vladislavleva, Member, IEEE, Guido F. Smits, Member, IEEE, and Dick den Hertog" + Environment.NewLine
    3434        + "Function: F3(X1, X2) = exp(-X1) * X1³ * cos(X1) * sin(X1) * (cos(X1)sin(X1)² - 1)(X2 - 5)" + Environment.NewLine
    35         + "Training Data: 601 points X1 = (0.05:0.1:10), X2 = (0.05:2:10.05)" + Environment.NewLine
    36         + "Test Data: 4840 points X1 = (-0.5:0.05:10.5), X2 = (-0.5:0.5:10.5)" + Environment.NewLine
     35        + "Training Data: 600 points X1 = (0.05:0.1:10), X2 = (0.05:2:10.05)" + Environment.NewLine
     36        + "Test Data: 221 * 23 points X1 = (-0.5:0.05:10.5), X2 = (-0.5:0.5:10.5)" + Environment.NewLine
    3737        + "Function Set: +, -, *, /, square, e^x, e^-x, sin(x), cos(x), x^eps, x + eps, x + eps";
    3838      }
    … …  
    4242    protected override string[] AllowedInputVariables { get { return new string[] { "X1", "X2" }; } }
    4343    protected override int TrainingPartitionStart { get { return 0; } }
    44     protected override int TrainingPartitionEnd { get { return 601; } }
    45     protected override int TestPartitionStart { get { return 601; } }
    46     protected override int TestPartitionEnd { get { return 5441; } }
     44    protected override int TrainingPartitionEnd { get { return 600; } }
     45    protected override int TestPartitionStart { get { return 600; } }
     46    protected override int TestPartitionEnd { get { return 600 + (221 * 23); } }
    4747
    4848    protected override List<List<double>> GenerateValues() {

  • trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Vladislavleva/SineCosineFunction.cs

    r8825 r8999  
    3434        + "Function: F6(X1, X2) = 6 * sin(X1) * cos(X2)" + Environment.NewLine
    3535        + "Training Data: 30 points X1, X2 = Rand(0.1, 5.9)" + Environment.NewLine
    36         + "Test Data: 961 points X1, X2 = (-0.05:0.02:6.05)" + Environment.NewLine
     36        + "Test Data: 306*306 points X1, X2 = (-0.05:0.02:6.05)" + Environment.NewLine
    3737        + "Function Set: +, -, *, /, square, e^x, e^-x, x^eps, x + eps, x * eps";
    3838      }
    … …  
    4343    protected override int TrainingPartitionStart { get { return 0; } }
    4444    protected override int TrainingPartitionEnd { get { return 30; } }
    45     protected override int TestPartitionStart { get { return 500; } }
    46     protected override int TestPartitionEnd { get { return 1461; } }
     45    protected override int TestPartitionStart { get { return 30; } }
     46    protected override int TestPartitionEnd { get { return 30 + (306 * 306); } }
    4747
    4848    protected override List<List<double>> GenerateValues() {
    … …  
    5353
    5454      for (int i = 0; i < AllowedInputVariables.Count(); i++) {
    55         data.Add(ValueGenerator.GenerateUniformDistributedValues(500, 0.1, 5.9).ToList());
     55        data.Add(ValueGenerator.GenerateUniformDistributedValues(30, 0.1, 5.9).ToList());
    5656        data[i].AddRange(combinations[i]);
    5757      }
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