Changeset 8225 for trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Korns/KornsFunctionNine.cs

Timestamp:

07/05/12 11:11:40 (13 years ago)

Author:

gkronber

Message:

#1784: Adapted Korns instances.

File:

• trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Korns/KornsFunctionNine.cs (modified) (2 diffs)

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

@@ -27 +27 @@
   public class KornsFunctionNine : ArtificialRegressionDataDescriptor {
 
-    public override string Name { get { return "Korns 9 y = ((sqrt(X0) / log(X1)) * (exp(X2) / square(X3)))"; } }
+    public override string Name { get { return "Korns 9 y = ((sqrt(X0) / log(X1)) * (exp(X2) / X3²)"; } }
     public override string Description {
       get {
         return "Paper: Accuracy in Symbolic Regression" + Environment.NewLine
         + "Authors: Michael F. Korns" + Environment.NewLine
-        + "Function: y = ((sqrt(X0) / log(X1)) * (exp(X2) / square(X3)))" + Environment.NewLine
-        + "Real Numbers: 3.45, -.982, 100.389, and all other real constants" + Environment.NewLine
-        + "Row Features: x1, x2, x9, and all other features" + Environment.NewLine
-        + "Binary Operators: +, -, *, /" + Environment.NewLine
-        + "Unary Operators: sqrt, square, cube, cos, sin, tan, tanh, log, exp" + Environment.NewLine
+        + "Function: y = (sqrt(X0) / log(X1)) * (exp(X2) / X3²)" + Environment.NewLine
+        + "Binary Operators: +, -, *, % (protected division)" + Environment.NewLine
+        + "Unary Operators: sqrt, square, cube, cos, sin, tan, tanh, ln(|x|) (protected log), exp" + Environment.NewLine
+        + "Constants: random finit 64-bit IEEE double" + Environment.NewLine
         + "\"Our testing regimen uses only statistical best practices out-of-sample testing techniques. "
         + "We test each of the test cases on matrices of 10000 rows by 1 to 5 columns with no noise. "
@@ -48 +47 @@
     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() {
       List<List<double>> data = new List<List<double>>();
       for (int i = 0; i < AllowedInputVariables.Count(); i++) {
-        data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, 0, 50).ToList());
+        data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, -50, 50).ToList());
       }