Changeset 8900 for trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Korns

Timestamp:

11/12/12 13:51:49 (12 years ago)

Author:

sforsten

Message:

#1979:

• renamed Keijzer 1-3
• corrected training and test partition of Keijzer 9 and 10
• changed interval for some variables in Korn 7, 9, 15 to avoid infinity and NaN values

Location:

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

Files:

• KornsFunctionFiveteen.cs (modified) (2 diffs)
• KornsFunctionNine.cs (modified) (2 diffs)
• KornsFunctionSeven.cs (modified) (2 diffs)

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

@@ -40 +40 @@
         + "For each test a training matrix is filled with random numbers between -50 and +50. The test case "
         + "target expressions are limited to one basis function whose maximum depth is three grammar nodes.\"" + Environment.NewLine + Environment.NewLine
-        + "Note: Because of the logarithm only non-negatic values are created for the input variables!";
+        + "Note: Because of the logarithm and the exponential function as denominator only non-negatic values are created for their input variables!";
       }
     }
@@ -54 +54 @@
       List<List<double>> data = new List<List<double>>();
       data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, -50, 50).ToList());
-      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, 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

@@ -40 +40 @@
         + "For each test a training matrix is filled with random numbers between -50 and +50. The test case "
         + "target expressions are limited to one basis function whose maximum depth is three grammar nodes.\"" + Environment.NewLine + Environment.NewLine
-        + "Note: Because of the square root and the logarithm only non-negatic values are created for the input variables!";
+        + "Note: Because of the square root and the logarithm only non-negatic values are created for their input variables!" + Environment.NewLine
+        + "Because of the exponential function only only non-positive values are created for its input variable!";
       }
     }
@@ -55 +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, 50).ToList()); 
-      data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, -50, 50).ToList()); 
-      data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, -50, 50).ToList()); 
+      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());
 
       double x0, x1, x2, x3;

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

@@ -39 +39 @@
         + "We test each of the test cases on matrices of 10000 rows by 1 to 5 columns with no noise. "
         + "For each test a training matrix is filled with random numbers between -50 and +50. The test case "
-        + "target expressions are limited to one basis function whose maximum depth is three grammar nodes.\"";
+        + "target expressions are limited to one basis function whose maximum depth is three grammar nodes.\"" + Environment.NewLine
+        + "Note: Because of the exponential function only non-negatic values are created for its input variable!";
       }
     }
@@ -52 +53 @@
     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, -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, -50, 50).ToList());
+      data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, -50, 50).ToList());
+      data.Add(ValueGenerator.GenerateUniformDistributedValues(TestPartitionEnd, -50, 50).ToList());
 
       double x0;