Changeset 8224 for trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression

Timestamp:

07/05/12 09:44:06 (12 years ago)

Author:

gkronber

Message:

#1784: fixed uniform sampling. Adapted Nguyen instances.

Location:

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

Files:

• Keijzer/KeijzerInstanceProvider.cs (modified) (1 diff)
• Korns/KornsInstanceProvider.cs (modified) (1 diff)
• Nguyen/NguyenFunctionEight.cs (modified) (1 diff)
• Nguyen/NguyenFunctionEleven.cs (modified) (2 diffs)
• Nguyen/NguyenFunctionFive.cs (modified) (1 diff)
• Nguyen/NguyenFunctionFour.cs (modified) (1 diff)
• Nguyen/NguyenFunctionNine.cs (modified) (2 diffs)
• Nguyen/NguyenFunctionOne.cs (modified) (1 diff)
• Nguyen/NguyenFunctionSeven.cs (modified) (1 diff)
• Nguyen/NguyenFunctionSix.cs (modified) (1 diff)
• Nguyen/NguyenFunctionTen.cs (modified) (2 diffs)
• Nguyen/NguyenFunctionThree.cs (modified) (1 diff)
• Nguyen/NguyenFunctionTwelve.cs (modified) (2 diffs)
• Nguyen/NguyenFunctionTwo.cs (modified) (1 diff)
• Nguyen/NguyenInstanceProvider.cs (modified) (1 diff)
• ValueGenerator.cs (modified) (2 diffs)
• Vladislavleva/VladislavlevaInstanceProvider.cs (modified) (1 diff)

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

@@ -35 +35 @@
     }
     public override string ReferencePublication {
-      get { return ""; }
+      get { return "McDermott et al., 2012 \"Genetic Programming Needs Better Benchmarks\", in Proc. of GECCO 2012."; }
     }
 

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

@@ -35 +35 @@
     }
     public override string ReferencePublication {
-      get { return ""; }
+      get { return "McDermott et al., 2012 \"Genetic Programming Needs Better Benchmarks\", in Proc. of GECCO 2012."; }
     }
 

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

@@ -33 +33 @@
         + "Authors: Nguyen Quang Uy · Nguyen Xuan Hoai · Michael O’Neill · R.I. McKay · Edgar Galvan-Lopez" + Environment.NewLine
         + "Function: F8 = Sqrt(x)" + Environment.NewLine
-        + "Fitcases: 20 random points ⊆ [0, 4]" + Environment.NewLine
-        + "Non-terminals: +, -, *, /, sin, cos, exp, log (protected version)" + Environment.NewLine
-        + "Terminals: X, 1 for single variable problems, and X, Y for bivariable problems";
+        + "Fitcases: 20 random points in [0, 4]" + Environment.NewLine
+        + "Non-terminals: +, -, *, % (protected division), sin, cos, exp, ln(|x|) (protected log)" + Environment.NewLine
+        + "Terminals: only variables (no random constants)";
       }
     }

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

@@ -33 +33 @@
         + "Authors: Nguyen Quang Uy · Nguyen Xuan Hoai · Michael O’Neill · R.I. McKay · Edgar Galvan-Lopez" + Environment.NewLine
         + "Function: F11 = x^y" + Environment.NewLine
-        + "Fitcases: 100 random points ⊆ [0, 1]x[0, 1]" + Environment.NewLine
-        + "Non-terminals: +, -, *, /, sin, cos, exp, log (protected version)" + Environment.NewLine
-        + "Terminals: X, 1 for single variable problems, and X, Y for bivariable problems";
+        + "Fitcases: 20 random points in [0, 1]x[0, 1]" + Environment.NewLine
+        + "Non-terminals: +, -, *, % (protected division), sin, cos, exp, ln(|x|) (protected log)" + Environment.NewLine
+        + "Terminals: only variables (no random constants)";
       }
     }
@@ -42 +42 @@
     protected override string[] AllowedInputVariables { get { return new string[] { "X", "Y" }; } }
     protected override int TrainingPartitionStart { get { return 0; } }
-    protected override int TrainingPartitionEnd { get { return 100; } }
+    protected override int TrainingPartitionEnd { get { return 20; } }
     protected override int TestPartitionStart { get { return 500; } }
     protected override int TestPartitionEnd { get { return 1000; } }

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

@@ -27 +27 @@
   public class NguyenFunctionFive : ArtificialRegressionDataDescriptor {
 
-    public override string Name { get { return "Nguyen F5 = sin(x^2)cos(x) - 1"; } }
+    public override string Name { get { return "Nguyen F5 = sin(x²)cos(x) - 1"; } }
     public override string Description {
       get {
         return "Paper: Semantically-based Crossover in Genetic Programming: Application to Real-valued Symbolic Regression" + Environment.NewLine
         + "Authors: Nguyen Quang Uy · Nguyen Xuan Hoai · Michael O’Neill · R.I. McKay · Edgar Galvan-Lopez" + Environment.NewLine
-        + "Function: F5 = sin(x^2)cos(x) - 1" + Environment.NewLine
-        + "Fitcases: 20 random points ⊆ [-1, 1]" + Environment.NewLine
-        + "Non-terminals: +, -, *, /, sin, cos, exp, log (protected version)" + Environment.NewLine
-        + "Terminals: X, 1 for single variable problems, and X, Y for bivariable problems";
+        + "Function: F5 = sin(x²)cos(x) - 1" + Environment.NewLine
+        + "Fitcases: 20 random points in [-1, 1]" + Environment.NewLine
+        + "Non-terminals: +, -, *, % (protected division), sin, cos, exp, ln(|x|) (protected log)" + Environment.NewLine
+        + "Terminals: only variables (no random constants)";
       }
     }

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

@@ -27 +27 @@
   public class NguyenFunctionFour : ArtificialRegressionDataDescriptor {
 
-    public override string Name { get { return "Nguyen F4 = x^6 + x^5 + x^4 + x^3 + x^2 + x"; } }
+    public override string Name { get { return "Nguyen F4 = x^6 + x^5 + x^4 + x³ + x² + x"; } }
     public override string Description {
       get {
         return "Paper: Semantically-based Crossover in Genetic Programming: Application to Real-valued Symbolic Regression" + Environment.NewLine
         + "Authors: Nguyen Quang Uy · Nguyen Xuan Hoai · Michael O’Neill · R.I. McKay · Edgar Galvan-Lopez" + Environment.NewLine
-        + "Function: F4 = x^6 + x^5 + x^4 + x^3 + x^2 + x" + Environment.NewLine
-        + "Fitcases: 20 random points ⊆ [-1, 1]" + Environment.NewLine
-        + "Non-terminals: +, -, *, /, sin, cos, exp, log (protected version)" + Environment.NewLine
-        + "Terminals: X, 1 for single variable problems, and X, Y for bivariable problems";
+        + "Function: F4 = x^6 + x^5 + x^4 + x³ + x² + x" + Environment.NewLine
+        + "Fitcases: 20 random points in [-1, 1]" + Environment.NewLine
+        + "Non-terminals: +, -, *, % (protected division), sin, cos, exp, ln(|x|) (protected log)" + Environment.NewLine
+        + "Terminals: only variables (no random constants)";
       }
     }

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

@@ -27 +27 @@
   public class NguyenFunctionNine : ArtificialRegressionDataDescriptor {
 
-    public override string Name { get { return "Nguyen F9 = sin(x) + sin(y^2)"; } }
+    public override string Name { get { return "Nguyen F9 = sin(x) + sin(y²)"; } }
     public override string Description {
       get {
         return "Paper: Semantically-based Crossover in Genetic Programming: Application to Real-valued Symbolic Regression" + Environment.NewLine
         + "Authors: Nguyen Quang Uy · Nguyen Xuan Hoai · Michael O’Neill · R.I. McKay · Edgar Galvan-Lopez" + Environment.NewLine
-        + "Function: F9 = sin(x) + sin(y^2)" + Environment.NewLine
-        + "Fitcases: 100 random points ⊆ [0, 1]x[0, 1]" + Environment.NewLine
-        + "Non-terminals: +, -, *, /, sin, cos, exp, log (protected version)" + Environment.NewLine
-        + "Terminals: X, 1 for single variable problems, and X, Y for bivariable problems";
+        + "Function: F9 = sin(x) + sin(y²)" + Environment.NewLine
+        + "Fitcases: 20 random points in [0, 1]x[0, 1]" + Environment.NewLine
+        + "Non-terminals: +, -, *, % (protected division), sin, cos, exp, ln(|x|) (protected log)" + Environment.NewLine
+        + "Terminals: only variables (no random constants)";
       }
     }
@@ -42 +42 @@
     protected override string[] AllowedInputVariables { get { return new string[] { "X", "Y" }; } }
     protected override int TrainingPartitionStart { get { return 0; } }
-    protected override int TrainingPartitionEnd { get { return 100; } }
+    protected override int TrainingPartitionEnd { get { return 20; } }
     protected override int TestPartitionStart { get { return 500; } }
     protected override int TestPartitionEnd { get { return 1000; } }

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

@@ -27 +27 @@
   public class NguyenFunctionOne : ArtificialRegressionDataDescriptor {
 
-    public override string Name { get { return "Nguyen F1 = x^3 + x^2 + x"; } }
+    public override string Name { get { return "Nguyen F1 = x³ + x² + x"; } }
     public override string Description {
       get {
         return "Paper: Semantically-based Crossover in Genetic Programming: Application to Real-valued Symbolic Regression" + Environment.NewLine
         + "Authors: Nguyen Quang Uy · Nguyen Xuan Hoai · Michael O’Neill · R.I. McKay · Edgar Galvan-Lopez" + Environment.NewLine
-        + "Function: F1 = x^3 + x^2 + x" + Environment.NewLine
-        + "Fitcases: 20 random points ⊆ [-1, 1]" + Environment.NewLine
-        + "Non-terminals: +, -, *, /, sin, cos, exp, log (protected version)" + Environment.NewLine
-        + "Terminals: X, 1 for single variable problems, and X, Y for bivariable problems";
+        + "Function: F1 = x³ + x² + x" + Environment.NewLine
+        + "Fitcases: 20 random points in [-1, 1]" + Environment.NewLine
+        + "Non-terminals: +, -, *, % (protected division), sin, cos, exp, ln(|x|) (protected log)" + Environment.NewLine
+        + "Terminals: only variables (no random constants)";
       }
     }

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

@@ -27 +27 @@
   public class NguyenFunctionSeven : ArtificialRegressionDataDescriptor {
 
-    public override string Name { get { return "Nguyen F7 = log(x + 1) + log(x^2 + 1)"; } }
+    public override string Name { get { return "Nguyen F7 = log(x + 1) + log(x² + 1)"; } }
     public override string Description {
       get {
         return "Paper: Semantically-based Crossover in Genetic Programming: Application to Real-valued Symbolic Regression" + Environment.NewLine
         + "Authors: Nguyen Quang Uy · Nguyen Xuan Hoai · Michael O’Neill · R.I. McKay · Edgar Galvan-Lopez" + Environment.NewLine
-        + "Function: F7 = log(x + 1) + log(x^2 + 1)" + Environment.NewLine
-        + "Fitcases: 20 random points ⊆ [0, 2]" + Environment.NewLine
-        + "Non-terminals: +, -, *, /, sin, cos, exp, log (protected version)" + Environment.NewLine
-        + "Terminals: X, 1 for single variable problems, and X, Y for bivariable problems";
+        + "Function: F7 = ln(x + 1) + ln(x² + 1)" + Environment.NewLine
+        + "Fitcases: 20 random points in [0, 2]" + Environment.NewLine
+        + "Non-terminals: +, -, *, % (protected division), sin, cos, exp, ln(|x|) (protected log)" + Environment.NewLine
+        + "Terminals: only variables (no random constants)";
       }
     }

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

@@ -27 +27 @@
   public class NguyenFunctionSix : ArtificialRegressionDataDescriptor {
 
-    public override string Name { get { return "Nguyen F6 = sin(x) + sin(x + x^2)"; } }
+    public override string Name { get { return "Nguyen F6 = sin(x) + sin(x + x²)"; } }
     public override string Description {
       get {
         return "Paper: Semantically-based Crossover in Genetic Programming: Application to Real-valued Symbolic Regression" + Environment.NewLine
         + "Authors: Nguyen Quang Uy · Nguyen Xuan Hoai · Michael O’Neill · R.I. McKay · Edgar Galvan-Lopez" + Environment.NewLine
-        + "Function: F6 = sin(x) + sin(x + x^2)" + Environment.NewLine
-        + "Fitcases: 20 random points ⊆ [-1, 1]" + Environment.NewLine
-        + "Non-terminals: +, -, *, /, sin, cos, exp, log (protected version)" + Environment.NewLine
-        + "Terminals: X, 1 for single variable problems, and X, Y for bivariable problems";
+        + "Function: F6 = sin(x) + sin(x + x²)" + Environment.NewLine
+        + "Fitcases: 20 random points in [-1, 1]" + Environment.NewLine
+        + "Non-terminals: +, -, *, % (protected division), sin, cos, exp, ln(|x|) (protected log)" + Environment.NewLine
+        + "Terminals: only variables (no random constants)";
       }
     }

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

@@ -33 +33 @@
         + "Authors: Nguyen Quang Uy · Nguyen Xuan Hoai · Michael O’Neill · R.I. McKay · Edgar Galvan-Lopez" + Environment.NewLine
         + "Function: F10 = 2sin(x)cos(y)" + Environment.NewLine
-        + "Fitcases: 100 random points ⊆ [0, 1]x[0, 1]" + Environment.NewLine
-        + "Non-terminals: +, -, *, /, sin, cos, exp, log (protected version)" + Environment.NewLine
-        + "Terminals: X, 1 for single variable problems, and X, Y for bivariable problems";
+        + "Fitcases: 20 random points in [0, 1]x[0, 1]" + Environment.NewLine
+        + "Non-terminals: +, -, *, % (protected division), sin, cos, exp, ln(|x|) (protected log)" + Environment.NewLine
+        + "Terminals: only variables (no random constants)";
       }
     }
@@ -42 +42 @@
     protected override string[] AllowedInputVariables { get { return new string[] { "X", "Y" }; } }
     protected override int TrainingPartitionStart { get { return 0; } }
-    protected override int TrainingPartitionEnd { get { return 100; } }
+    protected override int TrainingPartitionEnd { get { return 20; } }
     protected override int TestPartitionStart { get { return 500; } }
     protected override int TestPartitionEnd { get { return 1000; } }

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

@@ -27 +27 @@
   public class NguyenFunctionThree : ArtificialRegressionDataDescriptor {
 
-    public override string Name { get { return "Nguyen F3 = x^5 + x^4 + x^3 + x^2 + x"; } }
+    public override string Name { get { return "Nguyen F3 = x^5 + x^4 + x³ + x² + x"; } }
     public override string Description {
       get {
         return "Paper: Semantically-based Crossover in Genetic Programming: Application to Real-valued Symbolic Regression" + Environment.NewLine
         + "Authors: Nguyen Quang Uy · Nguyen Xuan Hoai · Michael O’Neill · R.I. McKay · Edgar Galvan-Lopez" + Environment.NewLine
-        + "Function: F3 = x^5 + x^4 + x^3 + x^2 + x" + Environment.NewLine
-        + "Fitcases: 20 random points ⊆ [-1, 1]" + Environment.NewLine
-        + "Non-terminals: +, -, *, /, sin, cos, exp, log (protected version)" + Environment.NewLine
-        + "Terminals: X, 1 for single variable problems, and X, Y for bivariable problems";
+        + "Function: F3 = x^5 + x^4 + x³ + x² + x" + Environment.NewLine
+        + "Fitcases: 20 random points in [-1, 1]" + Environment.NewLine
+        + "Non-terminals: +, -, *, % (protected division), sin, cos, exp, ln(|x|) (protected log)" + Environment.NewLine
+        + "Terminals: only variables (no random constants)";
       }
     }

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

@@ -27 +27 @@
   public class NguyenFunctionTwelve : ArtificialRegressionDataDescriptor {
 
-    public override string Name { get { return "Nguyen F12 = x^4 - x^3 + y^2/2 - y"; } }
+    public override string Name { get { return "Nguyen F12 = x^4 - x³ + y²/2 - y"; } }
     public override string Description {
       get {
         return "Paper: Semantically-based Crossover in Genetic Programming: Application to Real-valued Symbolic Regression" + Environment.NewLine
         + "Authors: Nguyen Quang Uy · Nguyen Xuan Hoai · Michael O’Neill · R.I. McKay · Edgar Galvan-Lopez" + Environment.NewLine
-        + "Function: F12 = x^4 - x^3 + y^2/2 - y" + Environment.NewLine
-        + "Fitcases: 100 random points ⊆ [0, 1]x[0, 1]" + Environment.NewLine
-        + "Non-terminals: +, -, *, /, sin, cos, exp, log (protected version)" + Environment.NewLine
-        + "Terminals: X, 1 for single variable problems, and X, Y for bivariable problems";
+        + "Function: F12 = x^4 - x³ + y²/2 - y" + Environment.NewLine
+        + "Fitcases: 20 random points in [0, 1]x[0, 1]" + Environment.NewLine
+        + "Non-terminals: +, -, *, % (protected division), sin, cos, exp, ln(|x|) (protected log)" + Environment.NewLine
+        + "Terminals: only variables (no random constants)";
       }
     }
@@ -42 +42 @@
     protected override string[] AllowedInputVariables { get { return new string[] { "X", "Y" }; } }
     protected override int TrainingPartitionStart { get { return 0; } }
-    protected override int TrainingPartitionEnd { get { return 100; } }
+    protected override int TrainingPartitionEnd { get { return 20; } }
     protected override int TestPartitionStart { get { return 500; } }
     protected override int TestPartitionEnd { get { return 1000; } }

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

@@ -27 +27 @@
   public class NguyenFunctionTwo : ArtificialRegressionDataDescriptor {
 
-    public override string Name { get { return "Nguyen F2 = x^4 + x^3 + x^2 + x"; } }
+    public override string Name { get { return "Nguyen F2 = x^4 + x³ + x² + x"; } }
     public override string Description {
       get {
         return "Paper: Semantically-based Crossover in Genetic Programming: Application to Real-valued Symbolic Regression" + Environment.NewLine
         + "Authors: Nguyen Quang Uy · Nguyen Xuan Hoai · Michael O’Neill · R.I. McKay · Edgar Galvan-Lopez" + Environment.NewLine
-        + "Function: F2 = x^4 + x^3 + x^2 + x" + Environment.NewLine
-        + "Fitcases: 20 random points ⊆ [-1, 1]" + Environment.NewLine
-        + "Non-terminals: +, -, *, /, sin, cos, exp, log (protected version)" + Environment.NewLine
-        + "Terminals: X, 1 for single variable problems, and X, Y for bivariable problems";
+        + "Function: F2 = x^4 + x³ + x² + x" + Environment.NewLine
+        + "Fitcases: 20 random points in [-1, 1]" + Environment.NewLine
+        + "Non-terminals: +, -, *, % (protected division), sin, cos, exp, ln(|x|) (protected log)" + Environment.NewLine
+        + "Terminals: only variables (no random constants)";
       }
     }

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

@@ -35 +35 @@
     }
     public override string ReferencePublication {
-      get { return ""; }
+      get { return "McDermott et al., 2012 \"Genetic Programming Needs Better Benchmarks\", in Proc. of GECCO 2012."; }
     }
 

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

@@ -29 +29 @@
     private static FastRandom rand = new FastRandom();
 
+    /// <summary>
+    /// Generates a sequence of evenly spaced points between start and end (inclusive!).
+    /// </summary>
+    /// <param name="start">The smallest and first value of the sequence.</param>
+    /// <param name="end">The largest and last value of the sequence.</param>
+    /// <param name="stepWidth">The step size between subsequent values.</param>
+    /// <returns>An sequence of values from start to end (inclusive)</returns>
     public static IEnumerable<double> GenerateSteps(double start, double end, double stepWidth) {
-      int steps = (int)Math.Round(((end - start) / stepWidth) + 1);
-      for (int i = 0; i < steps; i++)
-        yield return start + i * stepWidth;
+      if (start > end) throw new ArgumentException("start must be less than or equal end.");
+      if (stepWidth <= 0) throw new ArgumentException("stepwith must be larger than zero.", "stepWidth");
+      double x = start;
+      while (x <= end) {
+        yield return x;
+        x += stepWidth;
+      }
     }
 
-    public static IEnumerable<double> GenerateUniformDistributedValues(int amount, double start, double end) {
-      for (int i = 0; i < amount; i++)
-        yield return rand.NextDouble() * (end - start) + start;
+    /// <summary>
+    /// Generates uniformly distributed values between start and end (inclusive!) 
+    /// </summary>
+    /// <param name="n">Number of values to generate.</param>
+    /// <param name="start">The lower value (inclusive)</param>
+    /// <param name="end">The upper value (inclusive)</param>
+    /// <returns>An enumerable including n values in [start, end]</returns>
+    public static IEnumerable<double> GenerateUniformDistributedValues(int n, double start, double end) {
+      for (int i = 0; i < n; i++) {
+        // we need to return a random value including end.
+        // so we cannot use rand.NextDouble() as it returns a value strictly smaller than 1.
+        double r = rand.NextUInt() / (double)uint.MaxValue;    // r \in [0,1]
+        yield return r * (end - start) + start;
+      }
     }
 
-    public static IEnumerable<double> GenerateNormalDistributedValues(int amount, double mu, double sigma) {
-      for (int i = 0; i < amount; i++)
+    /// <summary>
+    /// Generates normally distributed values sampling from N(mu, sigma) 
+    /// </summary>
+    /// <param name="n">Number of values to generate.</param>
+    /// <param name="mu">The mu parameter of the normal distribution</param>
+    /// <param name="sigma">The sigma parameter of the normal distribution</param>
+    /// <returns>An enumerable including n values ~ N(mu, sigma)</returns>
+    public static IEnumerable<double> GenerateNormalDistributedValues(int n, double mu, double sigma) {
+      for (int i = 0; i < n; i++)
         yield return NormalDistributedRandom.NextDouble(rand, mu, sigma);
     }
@@ -82 +111 @@
       }
     }
-
-    //recursive approach
-    /*public static IEnumerable<IEnumerable<double>> GenerateAllCombinationsOfValuesInLists(List<List<double>> lists) {
-      int cur = 0;
-      List<double> curCombination = new List<double>();
-      List<List<double>> allCombinations = new List<List<double>>();
-      for (int i = 0; i < lists.Count; i++) {
-        allCombinations.Add(new List<double>());
-      }
-      if (lists.Count() > cur) {
-        foreach (var item in lists[cur]) {
-          curCombination.Clear();
-          curCombination.Add(item);
-          GetCombination(lists, cur + 1, curCombination, allCombinations);
-        }
-      }
-      return allCombinations;
-    }
-
-    private static void GetCombination(List<List<double>> lists, int cur, List<double> curCombinations, List<List<double>> allCombinations) {
-      if (lists.Count > cur) {
-        foreach (var item in lists[cur]) {
-          if (curCombinations.Count > cur) {
-            curCombinations.RemoveAt(cur);
-          }
-          curCombinations.Add(item);
-          GetCombination(lists, cur + 1, curCombinations, allCombinations);
-        }
-      } else {
-        for (int i = 0; i < curCombinations.Count; i++) {
-          allCombinations[i].Add(curCombinations[i]);
-        }
-      }
-    }         */
-
-    //original
-    /*public static IEnumerable<IEnumerable<double>> GenerateAllCombinationsOfValuesInLists(List<List<double>> sets) {
-
-      var combinations = new List<List<double>>();
-
-      foreach (var value in sets[0])
-        combinations.Add(new List<double> { value });
-
-      foreach (var set in sets.Skip(1))
-        combinations = AddListToCombinations(combinations, set);
-
-      IEnumerable<IEnumerable<double>> res = (from i in Enumerable.Range(0, sets.Count)
-                                              select (from list in combinations
-                                                      select list.ElementAt(i)));
-
-      return res;
-    }
-
-    private static List<List<double>> AddListToCombinations
-         (List<List<double>> combinations, List<double> set) {
-      var newCombinations = from value in set
-                            from combination in combinations
-                            select new List<double>(combination) { value };
-
-      return newCombinations.ToList();
-    }    */
   }
 }

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

@@ -35 +35 @@
     }
     public override string ReferencePublication {
-      get { return ""; }
+      get { return "McDermott et al., 2012 \"Genetic Programming Needs Better Benchmarks\", in Proc. of GECCO 2012."; }
     }