Changeset 9007

Timestamp:

12/06/12 14:13:39 (11 years ago)

Author:

gkronber

Message:

#1979: cross-checked all regression problem instances with the GP benchmarks paper and adapted where I thought necessary.

Location:

trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression

Files:

• Keijzer/KeijzerFunctionEleven.cs (modified) (2 diffs)
• Keijzer/KeijzerFunctionFifteen.cs (modified) (3 diffs)
• Keijzer/KeijzerFunctionFourteen.cs (modified) (3 diffs)
• Keijzer/KeijzerFunctionSeven.cs (modified) (1 diff)
• Keijzer/KeijzerFunctionTen.cs (modified) (1 diff)
• Keijzer/KeijzerFunctionThirteen.cs (modified) (2 diffs)
• Keijzer/KeijzerFunctionTwelve.cs (modified) (2 diffs)
• Korns/KornsFunctionEleven.cs (modified) (2 diffs)
• Korns/KornsFunctionFiveteen.cs (modified) (1 diff)
• Korns/KornsFunctionNine.cs (modified) (1 diff)
• Korns/KornsFunctionSeven.cs (modified) (1 diff)
• Nguyen/NguyenFunctionEight.cs (modified) (1 diff)
• Nguyen/NguyenFunctionEleven.cs (modified) (1 diff)
• Nguyen/NguyenFunctionFive.cs (modified) (2 diffs)
• Nguyen/NguyenFunctionFour.cs (modified) (2 diffs)
• Nguyen/NguyenFunctionNine.cs (modified) (2 diffs)
• Nguyen/NguyenFunctionOne.cs (modified) (1 diff)
• Nguyen/NguyenFunctionSeven.cs (modified) (2 diffs)
• Nguyen/NguyenFunctionSix.cs (modified) (2 diffs)
• Nguyen/NguyenFunctionTen.cs (modified) (1 diff)
• Nguyen/NguyenFunctionThree.cs (modified) (1 diff)
• Nguyen/NguyenFunctionTwelve.cs (modified) (2 diffs)
• Nguyen/NguyenFunctionTwo.cs (modified) (2 diffs)

trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Keijzer/KeijzerFunctionEleven.cs

@@ -36 +36 @@
           + "range(train): 20 Training cases x,y = rnd(-3, 3)" + Environment.NewLine
           + "range(test): x,y = [-3:0.01:3]" + Environment.NewLine
-          + "Function Set: x + y, x * y, 1/x, -x, sqrt(x)" + Environment.NewLine + Environment.NewLine
-          + "Note: Test partition has been adjusted to only 100 random uniformly distributed test cases in the interval [-3, 3] (not ca. 360000 as described) "
-          + ", but 5000 cases are created";
+          + "Function Set: x + y, x * y, 1/x, -x, sqrt(x)";
       }
     }
@@ -46 +44 @@
     protected override int TrainingPartitionStart { get { return 0; } }
     protected override int TrainingPartitionEnd { get { return 20; } }
-    protected override int TestPartitionStart { get { return 2500; } }
-    protected override int TestPartitionEnd { get { return 2600; } }
+    protected override int TestPartitionStart { get { return 20; } }
+    protected override int TestPartitionEnd { get { return 20 + (601 * 601); } }
 
     protected override List<List<double>> GenerateValues() {
       List<List<double>> data = new List<List<double>>();
+      List<double> oneVariableTestData = ValueGenerator.GenerateSteps(-3, 3, 0.01).ToList();
+      List<List<double>> testData = new List<List<double>>() { oneVariableTestData, oneVariableTestData };
+
+      var combinations = ValueGenerator.GenerateAllCombinationsOfValuesInLists(testData).ToList();
+
       for (int i = 0; i < AllowedInputVariables.Count(); i++) {
-        data.Add(ValueGenerator.GenerateUniformDistributedValues(5020, -3, 3).ToList());
+        data.Add(ValueGenerator.GenerateUniformDistributedValues(20, -3, 3).ToList());
+        data[i].AddRange(combinations[i]);
       }
 

trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Keijzer/KeijzerFunctionFifteen.cs

@@ -35 +35 @@
         + "range(train): 20 Training cases x,y = rnd(-3, 3)" + Environment.NewLine
         + "range(test): x,y = [-3:0.01:3]" + Environment.NewLine
-        + "Function Set: x + y, x * y, 1/x, -x, sqrt(x)" + Environment.NewLine + Environment.NewLine
-        + "Note: Test partition has been adjusted to only 100 random uniformly distributed test cases in the interval [-3, 3] (not ca. 360000 as described) "
-        + ", but 5000 cases are created";
+        + "Function Set: x + y, x * y, 1/x, -x, sqrt(x)";
       }
     }
@@ -45 +43 @@
     protected override int TrainingPartitionStart { get { return 0; } }
     protected override int TrainingPartitionEnd { get { return 20; } }
-    protected override int TestPartitionStart { get { return 2500; } }
-    protected override int TestPartitionEnd { get { return 2600; } }
+    protected override int TestPartitionStart { get { return 20; } }
+    protected override int TestPartitionEnd { get { return 20 + (601 * 601); } }
 
     protected override List<List<double>> GenerateValues() {
       List<List<double>> data = new List<List<double>>();
+      List<double> oneVariableTestData = ValueGenerator.GenerateSteps(-3, 3, 0.01).ToList();
+      List<List<double>> testData = new List<List<double>>() { oneVariableTestData, oneVariableTestData };
+
+      var combinations = ValueGenerator.GenerateAllCombinationsOfValuesInLists(testData).ToList();
+
       for (int i = 0; i < AllowedInputVariables.Count(); i++) {
-        data.Add(ValueGenerator.GenerateUniformDistributedValues(5000, -3, 3).ToList());
+        data.Add(ValueGenerator.GenerateUniformDistributedValues(20, -3, 3).ToList());
+        data[i].AddRange(combinations[i]);
       }
 
@@ -59 +63 @@
         x = data[0][i];
         y = data[1][i];
-        results.Add(Math.Pow(x, 3) / 5 + Math.Pow(y, 3) / 2 - y - x);
+        results.Add(x * x * x / 5.0 + y * y * y / 2.0 - y - x);
       }
       data.Add(results);

trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Keijzer/KeijzerFunctionFourteen.cs

@@ -35 +35 @@
         + "range(train): 20 Train cases x,y = rnd(-3, 3)" + Environment.NewLine
         + "range(test): x,y = [-3:0.01:3]" + Environment.NewLine
-        + "Function Set: x + y, x * y, 1/x, -x, sqrt(x)" + Environment.NewLine + Environment.NewLine
-        + "Note: Test partition has been adjusted to only 100 random uniformly distributed test cases in the interval [-3, 3] (not ca. 360000 as described) "
-        + ", but 5000 cases are created";
+        + "Function Set: x + y, x * y, 1/x, -x, sqrt(x)";
       }
     }
@@ -45 +43 @@
     protected override int TrainingPartitionStart { get { return 0; } }
     protected override int TrainingPartitionEnd { get { return 20; } }
-    protected override int TestPartitionStart { get { return 2500; } }
-    protected override int TestPartitionEnd { get { return 2600; } }
+    protected override int TestPartitionStart { get { return 20; } }
+    protected override int TestPartitionEnd { get { return 20 + (601 * 601); } }
 
     protected override List<List<double>> GenerateValues() {
       List<List<double>> data = new List<List<double>>();
+      List<double> oneVariableTestData = ValueGenerator.GenerateSteps(-3, 3, 0.01).ToList();
+      List<List<double>> testData = new List<List<double>>() { oneVariableTestData, oneVariableTestData };
+
+      var combinations = ValueGenerator.GenerateAllCombinationsOfValuesInLists(testData).ToList();
+
       for (int i = 0; i < AllowedInputVariables.Count(); i++) {
-        data.Add(ValueGenerator.GenerateUniformDistributedValues(5000, -3, 3).ToList());
+        data.Add(ValueGenerator.GenerateUniformDistributedValues(20, -3, 3).ToList());
+        data[i].AddRange(combinations[i]);
       }
 
@@ -59 +63 @@
         x = data[0][i];
         y = data[1][i];
-        results.Add(8 / (2 + Math.Pow(x, 2) + Math.Pow(y, 2)));
+        results.Add(8.0 / (2.0 + x * x + y * y));
       }
       data.Add(results);

trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Keijzer/KeijzerFunctionSeven.cs

@@ -36 +36 @@
           + "range(test): x = [1:0.1:100]" + Environment.NewLine
           + "Function Set: x + y, x * y, 1/x, -x, sqrt(x)" + Environment.NewLine + Environment.NewLine
-          + "Note: The problem starts with 1 to avoid log(0), which is minus infinity!";
+          + "Note: The problem starts with 1 to avoid log(0)!";
       }
     }

trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Keijzer/KeijzerFunctionTen.cs

@@ -44 +44 @@
     protected override int TrainingPartitionEnd { get { return 100; } }
     protected override int TestPartitionStart { get { return 100; } }
-    protected override int TestPartitionEnd { get { return 10301; } }
+    protected override int TestPartitionEnd { get { return 100 + (101 * 101); } }
 
     protected override List<List<double>> GenerateValues() {

trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Keijzer/KeijzerFunctionThirteen.cs

@@ -35 +35 @@
         + "range(train): 20 Train cases x,y = rnd(-3, 3)" + Environment.NewLine
         + "range(test): x,y = [-3:0.01:3]" + Environment.NewLine
-        + "Function Set: x + y, x * y, 1/x, -x, sqrt(x)" + Environment.NewLine + Environment.NewLine
-        + "Note: Test partition has been adjusted to only 100 random uniformly distributed test cases in the interval [-3, 3] (not ca. 360000 as described) "
-        + ", but 5000 cases are created";
+        + "Function Set: x + y, x * y, 1/x, -x, sqrt(x)";
       }
     }
@@ -45 +43 @@
     protected override int TrainingPartitionStart { get { return 0; } }
     protected override int TrainingPartitionEnd { get { return 20; } }
-    protected override int TestPartitionStart { get { return 2500; } }
-    protected override int TestPartitionEnd { get { return 2600; } }
+    protected override int TestPartitionStart { get { return 20; } }
+    protected override int TestPartitionEnd { get { return 20 + (601 * 601); } }
 
     protected override List<List<double>> GenerateValues() {
       List<List<double>> data = new List<List<double>>();
+      List<double> oneVariableTestData = ValueGenerator.GenerateSteps(-3, 3, 0.01).ToList();
+      List<List<double>> testData = new List<List<double>>() { oneVariableTestData, oneVariableTestData };
+
+      var combinations = ValueGenerator.GenerateAllCombinationsOfValuesInLists(testData).ToList();
+
       for (int i = 0; i < AllowedInputVariables.Count(); i++) {
-        data.Add(ValueGenerator.GenerateUniformDistributedValues(5000, -3, 3).ToList());
+        data.Add(ValueGenerator.GenerateUniformDistributedValues(20, -3, 3).ToList());
+        data[i].AddRange(combinations[i]);
       }
 

trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Keijzer/KeijzerFunctionTwelve.cs

@@ -31 +31 @@
       get {
         return "Paper: Improving Symbolic Regression with Interval Arithmetic and Linear Scaling" + Environment.NewLine
-        + "Authors: Maarten Keijzer" + Environment.NewLine
-        + "Function: f(x, y) = x^4 - x³ + y² / 2 - y" + Environment.NewLine
-        + "range(train): 20 Training cases x,y = rnd(-3, 3)" + Environment.NewLine
-        + "range(test): x,y = [-3:0.01:3]" + Environment.NewLine
-        + "Function Set: x + y, x * y, 1/x, -x, sqrt(x)" + Environment.NewLine + Environment.NewLine
-        + "Note: Test partition has been adjusted to only 100 random uniformly distributed test cases in the interval [-3, 3] (not ca. 360000 as described) "
-        + ", but 5000 cases are created";
+               + "Authors: Maarten Keijzer" + Environment.NewLine
+               + "Function: f(x, y) = x^4 - x³ + y² / 2 - y" + Environment.NewLine
+               + "range(train): 20 Training cases x,y = rnd(-3, 3)" + Environment.NewLine
+               + "range(test): x,y = [-3:0.01:3]" + Environment.NewLine
+               + "Function Set: x + y, x * y, 1/x, -x, sqrt(x)";
       }
     }
@@ -45 +43 @@
     protected override int TrainingPartitionStart { get { return 0; } }
     protected override int TrainingPartitionEnd { get { return 20; } }
-    protected override int TestPartitionStart { get { return 2500; } }
-    protected override int TestPartitionEnd { get { return 2600; } }
+    protected override int TestPartitionStart { get { return 20; } }
+    protected override int TestPartitionEnd { get { return 20 + (601 * 601); } }
 
     protected override List<List<double>> GenerateValues() {
       List<List<double>> data = new List<List<double>>();
+      List<double> oneVariableTestData = ValueGenerator.GenerateSteps(-3, 3, 0.01).ToList();
+      List<List<double>> testData = new List<List<double>>() { oneVariableTestData, oneVariableTestData };
+
+      var combinations = ValueGenerator.GenerateAllCombinationsOfValuesInLists(testData).ToList();
+
       for (int i = 0; i < AllowedInputVariables.Count(); i++) {
-        data.Add(ValueGenerator.GenerateUniformDistributedValues(5000, -3, 3).ToList());
+        data.Add(ValueGenerator.GenerateUniformDistributedValues(20, -3, 3).ToList());
+        data[i].AddRange(combinations[i]);
       }
 

trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Korns/KornsFunctionEleven.cs

@@ -27 +27 @@
   public class KornsFunctionEleven : ArtificialRegressionDataDescriptor {
 
-    public override string Name { get { return "Korns 11 y = 6.87 + (11 * cos(7.23 * X0 * X0 * X0))"; } }
+    public override string Name { get { return "Korns 11 y = 6.87 + (11 * cos(7.23 * X0³))"; } }
     public override string Description {
       get {
@@ -46 +46 @@
     protected override string[] AllowedInputVariables { get { return new string[] { "X0", "X1", "X2", "X3", "X4" }; } }
     protected override int TrainingPartitionStart { get { return 0; } }
-    protected override int TrainingPartitionEnd { get { return 5000; } }
-    protected override int TestPartitionStart { get { return 5000; } }
-    protected override int TestPartitionEnd { get { return 10000; } }
+    protected override int TrainingPartitionEnd { get { return 10000; } }
+    protected override int TestPartitionStart { get { return 10000; } }
+    protected override int TestPartitionEnd { get { return 20000; } }
 
     protected override List<List<double>> GenerateValues() {

trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Korns/KornsFunctionFiveteen.cs

@@ -54 +54 @@
       List<List<double>> data = new List<List<double>>();
       data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, -50, 50).ToList());
-      data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, 0, 50).ToList()); // note: range is only [0,50] to prevent NaN values (deviates from gp benchmark paper)
+      data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, -50, 50).ToList()); 
       data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, 0, 50).ToList()); // note: range is only [0,50] to prevent NaN values (deviates from gp benchmark paper)
       data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, -50, 50).ToList());

trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Korns/KornsFunctionNine.cs

@@ -56 +56 @@
       data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, 0, 50).ToList()); // note: range is only [0,50] to prevent NaN values (deviates from gp benchmark paper)
       data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, 0, 50).ToList()); // note: range is only [0,50] to prevent NaN values (deviates from gp benchmark paper)
-      data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, -50, 0).ToList()); // note: range is only [-50,0] to prevent NaN values (deviates from gp benchmark paper)
+      data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, -50, 50).ToList()); 
       data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, -50, 50).ToList());
       data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, -50, 50).ToList());

trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Korns/KornsFunctionSeven.cs

@@ -53 +53 @@
     protected override List<List<double>> GenerateValues() {
       List<List<double>> data = new List<List<double>>();
-      data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, 0, 50).ToList()); // note: range is only [0,50] to prevent NaN values (deviates from gp benchmark paper)
+      data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, -50, 50).ToList());
       data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, -50, 50).ToList());
       data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, -50, 50).ToList());

trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Nguyen/NguyenFunctionEight.cs

@@ -43 +43 @@
     protected override int TrainingPartitionStart { get { return 0; } }
     protected override int TrainingPartitionEnd { get { return 20; } }
-    protected override int TestPartitionStart { get { return 250; } }
-    protected override int TestPartitionEnd { get { return 350; } }
+    protected override int TestPartitionStart { get { return 20; } }
+    protected override int TestPartitionEnd { get { return 520; } }
 
     protected override List<List<double>> GenerateValues() {
       List<List<double>> data = new List<List<double>>();
-      data.Add(ValueGenerator.GenerateUniformDistributedValues(500, 0, 4).ToList());
+      data.Add(ValueGenerator.GenerateUniformDistributedValues(520, 0, 4).ToList());
 
       double x;

trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Nguyen/NguyenFunctionEleven.cs

@@ -43 +43 @@
     protected override int TrainingPartitionStart { get { return 0; } }
     protected override int TrainingPartitionEnd { get { return 20; } }
-    protected override int TestPartitionStart { get { return 500; } }
-    protected override int TestPartitionEnd { get { return 1000; } }
+    protected override int TestPartitionStart { get { return 20; } }
+    protected override int TestPartitionEnd { get { return 1020; } }
 
     protected override List<List<double>> GenerateValues() {

trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Nguyen/NguyenFunctionFive.cs

@@ -43 +43 @@
     protected override int TrainingPartitionStart { get { return 0; } }
     protected override int TrainingPartitionEnd { get { return 20; } }
-    protected override int TestPartitionStart { get { return 250; } }
-    protected override int TestPartitionEnd { get { return 350; } }
+    protected override int TestPartitionStart { get { return 20; } }
+    protected override int TestPartitionEnd { get { return 520; } }
 
     protected override List<List<double>> GenerateValues() {
       List<List<double>> data = new List<List<double>>();
-      data.Add(ValueGenerator.GenerateUniformDistributedValues(500, -1, 1).ToList());
+      data.Add(ValueGenerator.GenerateUniformDistributedValues(520, -1, 1).ToList());
 
       double x;
@@ -54 +54 @@
       for (int i = 0; i < data[0].Count; i++) {
         x = data[0][i];
-        results.Add(Math.Sin(Math.Pow(x, 2)) * Math.Cos(x) - 1);
+        results.Add(Math.Sin(x * x) * Math.Cos(x) - 1);
       }
       data.Add(results);

trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Nguyen/NguyenFunctionFour.cs

@@ -43 +43 @@
     protected override int TrainingPartitionStart { get { return 0; } }
     protected override int TrainingPartitionEnd { get { return 20; } }
-    protected override int TestPartitionStart { get { return 250; } }
-    protected override int TestPartitionEnd { get { return 350; } }
+    protected override int TestPartitionStart { get { return 20; } }
+    protected override int TestPartitionEnd { get { return 520; } }
 
     protected override List<List<double>> GenerateValues() {
       List<List<double>> data = new List<List<double>>();
-      data.Add(ValueGenerator.GenerateUniformDistributedValues(500, -1, 1).ToList());
+      data.Add(ValueGenerator.GenerateUniformDistributedValues(520, -1, 1).ToList());
 
       double x;
@@ -54 +54 @@
       for (int i = 0; i < data[0].Count; i++) {
         x = data[0][i];
-        results.Add(Math.Pow(x, 6) + Math.Pow(x, 5) + Math.Pow(x, 4) + Math.Pow(x, 3) + Math.Pow(x, 2) + x);
+        results.Add(Math.Pow(x, 6) + Math.Pow(x, 5) + Math.Pow(x, 4) + Math.Pow(x, 3) + x * x + x);
       }
       data.Add(results);

trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Nguyen/NguyenFunctionNine.cs

@@ -43 +43 @@
     protected override int TrainingPartitionStart { get { return 0; } }
     protected override int TrainingPartitionEnd { get { return 20; } }
-    protected override int TestPartitionStart { get { return 500; } }
-    protected override int TestPartitionEnd { get { return 1000; } }
+    protected override int TestPartitionStart { get { return 20; } }
+    protected override int TestPartitionEnd { get { return 1020; } }
 
     protected override List<List<double>> GenerateValues() {
@@ -56 +56 @@
         x = data[0][i];
         y = data[1][i];
-        results.Add(Math.Sin(x) + Math.Sin(Math.Pow(y, 2)));
+        results.Add(Math.Sin(x) + Math.Sin(y * y));
       }
       data.Add(results);

trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Nguyen/NguyenFunctionOne.cs

@@ -43 +43 @@
     protected override int TrainingPartitionStart { get { return 0; } }
     protected override int TrainingPartitionEnd { get { return 20; } }
-    protected override int TestPartitionStart { get { return 250; } }
-    protected override int TestPartitionEnd { get { return 350; } }
+    protected override int TestPartitionStart { get { return 20; } }
+    protected override int TestPartitionEnd { get { return 520; } }
 
     protected override List<List<double>> GenerateValues() {
       List<List<double>> data = new List<List<double>>();
-      data.Add(ValueGenerator.GenerateUniformDistributedValues(500, -1, 1).ToList());
+      data.Add(ValueGenerator.GenerateUniformDistributedValues(520, -1, 1).ToList());
 
       double x;

trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Nguyen/NguyenFunctionSeven.cs

@@ -43 +43 @@
     protected override int TrainingPartitionStart { get { return 0; } }
     protected override int TrainingPartitionEnd { get { return 20; } }
-    protected override int TestPartitionStart { get { return 250; } }
-    protected override int TestPartitionEnd { get { return 350; } }
+    protected override int TestPartitionStart { get { return 20; } }
+    protected override int TestPartitionEnd { get { return 520; } }
 
     protected override List<List<double>> GenerateValues() {
       List<List<double>> data = new List<List<double>>();
-      data.Add(ValueGenerator.GenerateUniformDistributedValues(500, 0, 2).ToList());
+      data.Add(ValueGenerator.GenerateUniformDistributedValues(520, 0, 2).ToList());
 
       double x;
@@ -54 +54 @@
       for (int i = 0; i < data[0].Count; i++) {
         x = data[0][i];
-        results.Add(Math.Log(x + 1) + Math.Log(Math.Pow(x, 2) + 1));
+        results.Add(Math.Log(x + 1) + Math.Log(x * x + 1));
       }
       data.Add(results);

trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Nguyen/NguyenFunctionSix.cs

@@ -43 +43 @@
     protected override int TrainingPartitionStart { get { return 0; } }
     protected override int TrainingPartitionEnd { get { return 20; } }
-    protected override int TestPartitionStart { get { return 250; } }
-    protected override int TestPartitionEnd { get { return 350; } }
+    protected override int TestPartitionStart { get { return 20; } }
+    protected override int TestPartitionEnd { get { return 520; } }
 
     protected override List<List<double>> GenerateValues() {
       List<List<double>> data = new List<List<double>>();
-      data.Add(ValueGenerator.GenerateUniformDistributedValues(500, -1, 1).ToList());
+      data.Add(ValueGenerator.GenerateUniformDistributedValues(520, -1, 1).ToList());
 
       double x;
@@ -54 +54 @@
       for (int i = 0; i < data[0].Count; i++) {
         x = data[0][i];
-        results.Add(Math.Sin(x) + Math.Sin(x + Math.Pow(x, 2)));
+        results.Add(Math.Sin(x) + Math.Sin(x + x*x));
       }
       data.Add(results);

trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Nguyen/NguyenFunctionTen.cs

@@ -43 +43 @@
     protected override int TrainingPartitionStart { get { return 0; } }
     protected override int TrainingPartitionEnd { get { return 20; } }
-    protected override int TestPartitionStart { get { return 500; } }
-    protected override int TestPartitionEnd { get { return 1000; } }
+    protected override int TestPartitionStart { get { return 20; } }
+    protected override int TestPartitionEnd { get { return 1020; } }
 
     protected override List<List<double>> GenerateValues() {
       List<List<double>> data = new List<List<double>>();
-      data.Add(ValueGenerator.GenerateUniformDistributedValues(1000, 0, 1).ToList());
-      data.Add(ValueGenerator.GenerateUniformDistributedValues(1000, 0, 1).ToList());
+      data.Add(ValueGenerator.GenerateUniformDistributedValues(1020, 0, 1).ToList());
+      data.Add(ValueGenerator.GenerateUniformDistributedValues(1020, 0, 1).ToList());
 
       double x, y;

trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Nguyen/NguyenFunctionThree.cs

@@ -43 +43 @@
     protected override int TrainingPartitionStart { get { return 0; } }
     protected override int TrainingPartitionEnd { get { return 20; } }
-    protected override int TestPartitionStart { get { return 250; } }
-    protected override int TestPartitionEnd { get { return 350; } }
+    protected override int TestPartitionStart { get { return 20; } }
+    protected override int TestPartitionEnd { get { return 520; } }
 
     protected override List<List<double>> GenerateValues() {
       List<List<double>> data = new List<List<double>>();
-      data.Add(ValueGenerator.GenerateUniformDistributedValues(500, -1, 1).ToList());
+      data.Add(ValueGenerator.GenerateUniformDistributedValues(520, -1, 1).ToList());
 
       double x;

trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Nguyen/NguyenFunctionTwelve.cs

@@ -43 +43 @@
     protected override int TrainingPartitionStart { get { return 0; } }
     protected override int TrainingPartitionEnd { get { return 20; } }
-    protected override int TestPartitionStart { get { return 500; } }
-    protected override int TestPartitionEnd { get { return 1000; } }
+    protected override int TestPartitionStart { get { return 20; } }
+    protected override int TestPartitionEnd { get { return 1020; } }
 
     protected override List<List<double>> GenerateValues() {
       List<List<double>> data = new List<List<double>>();
-      data.Add(ValueGenerator.GenerateUniformDistributedValues(1000, 0, 1).ToList());
-      data.Add(ValueGenerator.GenerateUniformDistributedValues(1000, 0, 1).ToList());
+      data.Add(ValueGenerator.GenerateUniformDistributedValues(1020, 0, 1).ToList());
+      data.Add(ValueGenerator.GenerateUniformDistributedValues(1020, 0, 1).ToList());
 
       double x, y;
@@ -56 +56 @@
         x = data[0][i];
         y = data[1][i];
-        results.Add(Math.Pow(x, 4) - Math.Pow(x, 3) + Math.Pow(y, 2) / 2 - y);
+        results.Add(Math.Pow(x, 4) - Math.Pow(x, 3) + y * y / 2 - y);
       }
       data.Add(results);

trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Nguyen/NguyenFunctionTwo.cs

@@ -43 +43 @@
     protected override int TrainingPartitionStart { get { return 0; } }
     protected override int TrainingPartitionEnd { get { return 20; } }
-    protected override int TestPartitionStart { get { return 250; } }
-    protected override int TestPartitionEnd { get { return 350; } }
+    protected override int TestPartitionStart { get { return 20; } }
+    protected override int TestPartitionEnd { get { return 520; } }
 
     protected override List<List<double>> GenerateValues() {
       List<List<double>> data = new List<List<double>>();
-      data.Add(ValueGenerator.GenerateUniformDistributedValues(500, -1, 1).ToList());
+      data.Add(ValueGenerator.GenerateUniformDistributedValues(520, -1, 1).ToList());
 
       double x;
@@ -54 +54 @@
       for (int i = 0; i < data[0].Count; i++) {
         x = data[0][i];
-        results.Add(Math.Pow(x, 4) + Math.Pow(x, 3) + Math.Pow(x, 2) + x);
+        results.Add(Math.Pow(x, 4) + Math.Pow(x, 3) + x*x + x);
       }
       data.Add(results);