Changeset 8999

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:

• KotanchekFunction.cs (modified) (2 diffs)
• RationalPolynomialThreeDimensional.cs (modified) (2 diffs)
• RationalPolynomialTwoDimensional.cs (modified) (3 diffs)
• RippleFunction.cs (modified) (2 diffs)
• SalutowiczFunctionTwoDimensional.cs (modified) (2 diffs)
• SineCosineFunction.cs (modified) (3 diffs)

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

@@ -34 +34 @@
         + "Function: F1(X1, X2) = exp(-(X1 - 1))² / (1.2 + (X2 -2.5)²" + Environment.NewLine
         + "Training Data: 100 points X1, X2 = Rand(0.3, 4)" + Environment.NewLine
-        + "Test Data: 2026 points (X1, X2) = (-0.2:0.1:4.2)" + Environment.NewLine
+        + "Test Data: 441*441 points (X1, X2) = (-0.2:0.01:4.2)" + Environment.NewLine
         + "Function Set: +, -, *, /, square, e^x, e^-x, x^eps, x + eps, x * eps";
       }
@@ -44 +44 @@
     protected override int TrainingPartitionEnd { get { return 100; } }
     protected override int TestPartitionStart { get { return 100; } }
-    protected override int TestPartitionEnd { get { return 2126; } }
+    protected override int TestPartitionEnd { get { return 100 + (441 * 441); } }
 
     protected override List<List<double>> GenerateValues() {
       List<List<double>> data = new List<List<double>>();
 
-      List<double> oneVariableTestData = ValueGenerator.GenerateSteps(-0.2, 4.2, 0.1).ToList();
+      List<double> oneVariableTestData = ValueGenerator.GenerateSteps(-0.2, 4.2, 0.01).ToList();
       List<List<double>> testData = new List<List<double>>() { oneVariableTestData, oneVariableTestData };
       var combinations = ValueGenerator.GenerateAllCombinationsOfValuesInLists(testData).ToList<IEnumerable<double>>();

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

@@ -34 +34 @@
         + "Function: F5(X1, X2, X3) = 30 * ((X1 - 1) * (X3 -1)) / (X2² * (X1 - 10))" + Environment.NewLine
         + "Training Data: 300 points X1, X3 = Rand(0.05, 2), X2 = Rand(1, 2)" + Environment.NewLine
-        + "Test Data: 2701 points X1, X3 = (-0.05:0.15:2.1), X2 = (0.95:0.1:2.05)" + Environment.NewLine
+        + "Test Data: (14*12*14) points X1, X3 = (-0.05:0.15:2.1), X2 = (0.95:0.1:2.05)" + Environment.NewLine
         + "Function Set: +, -, *, /, square, x^eps, x + eps, x * eps";
       }
@@ -43 +43 @@
     protected override int TrainingPartitionStart { get { return 0; } }
     protected override int TrainingPartitionEnd { get { return 300; } }
-    protected override int TestPartitionStart { get { return 1000; } }
-    protected override int TestPartitionEnd { get { return 3700; } }
+    protected override int TestPartitionStart { get { return 300; } }
+    protected override int TestPartitionEnd { get { return 300 + (14*12*14); } }
 
     protected override List<List<double>> GenerateValues() {
       List<List<double>> data = new List<List<double>>();
 
-      int n = 1000;
+      int n = 300;
       data.Add(ValueGenerator.GenerateUniformDistributedValues(n, 0.05, 2).ToList());
       data.Add(ValueGenerator.GenerateUniformDistributedValues(n, 1, 2).ToList());

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

@@ -34 +34 @@
         + "Function: F8(X1, X2) = ((X1 - 3)^4 + (X2 - 3)³ - (X2 -3)) / ((X2 - 2)^4 + 10)" + Environment.NewLine
         + "Training Data: 50 points X1, X2 = Rand(0.05, 6.05)" + Environment.NewLine
-        + "Test Data: 1157 points X1, X2 = (-0.25:0.2:6.35)" + Environment.NewLine
+        + "Test Data: 34*34 points X1, X2 = (-0.25:0.2:6.35)" + Environment.NewLine
         + "Function Set: +, -, *, /, square, x^eps, x + eps, x * eps";
       }
@@ -43 +43 @@
     protected override int TrainingPartitionStart { get { return 0; } }
     protected override int TrainingPartitionEnd { get { return 50; } }
-    protected override int TestPartitionStart { get { return 1000; } }
-    protected override int TestPartitionEnd { get { return 2157; } }
+    protected override int TestPartitionStart { get { return 50; } }
+    protected override int TestPartitionEnd { get { return 50 + (34 * 34); } }
 
     protected override List<List<double>> GenerateValues() {
@@ -50 +50 @@
 
       List<double> oneVariableTestData = ValueGenerator.GenerateSteps(-0.25, 6.35, 0.2).ToList();
+
       List<List<double>> testData = new List<List<double>>() { oneVariableTestData, oneVariableTestData };
+      var combinations = ValueGenerator.GenerateAllCombinationsOfValuesInLists(testData).ToList<IEnumerable<double>>();
 
-      var combinations = ValueGenerator.GenerateAllCombinationsOfValuesInLists(testData).ToList<IEnumerable<double>>();
       for (int i = 0; i < AllowedInputVariables.Count(); i++) {
-        data.Add(ValueGenerator.GenerateUniformDistributedValues(1000, 0.05, 6.05).ToList());
+        data.Add(ValueGenerator.GenerateUniformDistributedValues(50, 0.05, 6.05).ToList());
         data[i].AddRange(combinations[i]);
       }

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

@@ -27 +27 @@
   public class RippleFunction : ArtificialRegressionDataDescriptor {
 
-    public override string Name { get { return "Vladislavleva-7  F7(X1, X2) = (X1 - 3)(X2 - 3) + 2 * sin((X1 - 4)(X2 - 4))"; } }
+    public override string Name { get { return "Vladislavleva-7 F7(X1, X2) = (X1 - 3)(X2 - 3) + 2 * sin((X1 - 4)(X2 - 4))"; } }
     public override string Description {
       get {
@@ -44 +44 @@
     protected override int TrainingPartitionEnd { get { return 300; } }
     protected override int TestPartitionStart { get { return 300; } }
-    protected override int TestPartitionEnd { get { return 1300; } }
+    protected override int TestPartitionEnd { get { return 300 + 1000; } }
 
     protected override List<List<double>> GenerateValues() {
       List<List<double>> data = new List<List<double>>();
       for (int i = 0; i < AllowedInputVariables.Count(); i++) {
-        data.Add(ValueGenerator.GenerateUniformDistributedValues(TrainingPartitionEnd, 0.05, 6.05).ToList());
+        data.Add(ValueGenerator.GenerateUniformDistributedValues(300, 0.05, 6.05).ToList());
       }
 
       for (int i = 0; i < AllowedInputVariables.Count(); i++) {
-        data[i].AddRange(ValueGenerator.GenerateUniformDistributedValues(TrainingPartitionEnd, -0.25, 6.35));
+        data[i].AddRange(ValueGenerator.GenerateUniformDistributedValues(1000, -0.25, 6.35));
       }
 

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

@@ -33 +33 @@
         + "Authors: Ekaterina J. Vladislavleva, Member, IEEE, Guido F. Smits, Member, IEEE, and Dick den Hertog" + Environment.NewLine
         + "Function: F3(X1, X2) = exp(-X1) * X1³ * cos(X1) * sin(X1) * (cos(X1)sin(X1)² - 1)(X2 - 5)" + Environment.NewLine
-        + "Training Data: 601 points X1 = (0.05:0.1:10), X2 = (0.05:2:10.05)" + Environment.NewLine
-        + "Test Data: 4840 points X1 = (-0.5:0.05:10.5), X2 = (-0.5:0.5:10.5)" + Environment.NewLine
+        + "Training Data: 600 points X1 = (0.05:0.1:10), X2 = (0.05:2:10.05)" + Environment.NewLine
+        + "Test Data: 221 * 23 points X1 = (-0.5:0.05:10.5), X2 = (-0.5:0.5:10.5)" + Environment.NewLine
         + "Function Set: +, -, *, /, square, e^x, e^-x, sin(x), cos(x), x^eps, x + eps, x + eps";
       }
@@ -42 +42 @@
     protected override string[] AllowedInputVariables { get { return new string[] { "X1", "X2" }; } }
     protected override int TrainingPartitionStart { get { return 0; } }
-    protected override int TrainingPartitionEnd { get { return 601; } }
-    protected override int TestPartitionStart { get { return 601; } }
-    protected override int TestPartitionEnd { get { return 5441; } }
+    protected override int TrainingPartitionEnd { get { return 600; } }
+    protected override int TestPartitionStart { get { return 600; } }
+    protected override int TestPartitionEnd { get { return 600 + (221 * 23); } }
 
     protected override List<List<double>> GenerateValues() {

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

@@ -34 +34 @@
         + "Function: F6(X1, X2) = 6 * sin(X1) * cos(X2)" + Environment.NewLine
         + "Training Data: 30 points X1, X2 = Rand(0.1, 5.9)" + Environment.NewLine
-        + "Test Data: 961 points X1, X2 = (-0.05:0.02:6.05)" + Environment.NewLine
+        + "Test Data: 306*306 points X1, X2 = (-0.05:0.02:6.05)" + Environment.NewLine
         + "Function Set: +, -, *, /, square, e^x, e^-x, x^eps, x + eps, x * eps";
       }
@@ -43 +43 @@
     protected override int TrainingPartitionStart { get { return 0; } }
     protected override int TrainingPartitionEnd { get { return 30; } }
-    protected override int TestPartitionStart { get { return 500; } }
-    protected override int TestPartitionEnd { get { return 1461; } }
+    protected override int TestPartitionStart { get { return 30; } }
+    protected override int TestPartitionEnd { get { return 30 + (306 * 306); } }
 
     protected override List<List<double>> GenerateValues() {
@@ -53 +53 @@
 
       for (int i = 0; i < AllowedInputVariables.Count(); i++) {
-        data.Add(ValueGenerator.GenerateUniformDistributedValues(500, 0.1, 5.9).ToList());
+        data.Add(ValueGenerator.GenerateUniformDistributedValues(30, 0.1, 5.9).ToList());
         data[i].AddRange(combinations[i]);
       }