Changeset 7336 for branches/RegressionBenchmarks/HeuristicLab.Problems.DataAnalysis.Benchmarks/3.4

Timestamp:

01/16/12 17:02:55 (13 years ago)

Author:

sforsten

Message:

#1669:

• bug fixed in RegressionBenchmark
• adapted trainings partitions of some benchmark problems

Location:

branches/RegressionBenchmarks/HeuristicLab.Problems.DataAnalysis.Benchmarks/3.4

Files:

• RegressionBenchmarks/Keijzer/KeijzerFunctionFifteen.cs (modified) (1 diff)
• RegressionBenchmarks/Keijzer/KeijzerFunctionSixteen.cs (modified) (1 diff)
• RegressionBenchmarks/Keijzer/KeijzerFunctionThirteen.cs (modified) (1 diff)
• RegressionBenchmarks/Keijzer/KeijzerFunctionTwelve.cs (modified) (1 diff)
• RegressionBenchmarks/Nguyen/NguyenFunctionEight.cs (modified) (2 diffs)
• RegressionBenchmarks/Nguyen/NguyenFunctionEleven.cs (modified) (2 diffs)
• RegressionBenchmarks/Nguyen/NguyenFunctionFive.cs (modified) (2 diffs)
• RegressionBenchmarks/Nguyen/NguyenFunctionFour.cs (modified) (2 diffs)
• RegressionBenchmarks/Nguyen/NguyenFunctionNine.cs (modified) (2 diffs)
• RegressionBenchmarks/Nguyen/NguyenFunctionOne.cs (modified) (2 diffs)
• RegressionBenchmarks/Nguyen/NguyenFunctionSeven.cs (modified) (2 diffs)
• RegressionBenchmarks/Nguyen/NguyenFunctionSix.cs (modified) (2 diffs)
• RegressionBenchmarks/Nguyen/NguyenFunctionTen.cs (modified) (2 diffs)
• RegressionBenchmarks/Nguyen/NguyenFunctionThree.cs (modified) (2 diffs)
• RegressionBenchmarks/Nguyen/NguyenFunctionTwelve.cs (modified) (2 diffs)
• RegressionBenchmarks/Nguyen/NguyenFunctionTwo.cs (modified) (2 diffs)
• RegressionBenchmarks/Vladislavleva/KotanchekFunction.cs (modified) (3 diffs)
• RegressionBenchmarks/Vladislavleva/RationalPolynomialThreeDimensional.cs (modified) (2 diffs)
• RegressionBenchmarks/Vladislavleva/RationalPolynomialTwoDimensional.cs (modified) (3 diffs)
• RegressionBenchmarks/Vladislavleva/SineCosineFunction.cs (modified) (3 diffs)
• RegressionGenerator/RegressionBenchmark.cs (modified) (2 diffs)

branches/RegressionBenchmarks/HeuristicLab.Problems.DataAnalysis.Benchmarks/3.4/RegressionBenchmarks/Keijzer/KeijzerFunctionFifteen.cs

@@ -40 +40 @@
       inputVariables = new List<string>() { "X", "Y" };
       trainingPartition = new IntRange(0, 20);
-      testPartition = new IntRange(20, 120);
+      testPartition = new IntRange(2500, 2600);
     }
 

branches/RegressionBenchmarks/HeuristicLab.Problems.DataAnalysis.Benchmarks/3.4/RegressionBenchmarks/Keijzer/KeijzerFunctionSixteen.cs

@@ -40 +40 @@
       inputVariables = new List<string>() { "X", "Y" };
       trainingPartition = new IntRange(0, 20);
-      testPartition = new IntRange(20, 120);
+      testPartition = new IntRange(2500, 2600);
     }
 

branches/RegressionBenchmarks/HeuristicLab.Problems.DataAnalysis.Benchmarks/3.4/RegressionBenchmarks/Keijzer/KeijzerFunctionThirteen.cs

@@ -40 +40 @@
       inputVariables = new List<string>() { "X", "Y" };
       trainingPartition = new IntRange(0, 20);
-      testPartition = new IntRange(20, 120);
+      testPartition = new IntRange(2500, 2600);
     }
 

branches/RegressionBenchmarks/HeuristicLab.Problems.DataAnalysis.Benchmarks/3.4/RegressionBenchmarks/Keijzer/KeijzerFunctionTwelve.cs

@@ -40 +40 @@
       inputVariables = new List<string>() { "X", "Y" };
       trainingPartition = new IntRange(0, 20);
-      testPartition = new IntRange(20, 120);
+      testPartition = new IntRange(2500, 2600);
     }
 

branches/RegressionBenchmarks/HeuristicLab.Problems.DataAnalysis.Benchmarks/3.4/RegressionBenchmarks/Nguyen/NguyenFunctionEight.cs

@@ -37 +37 @@
       targetVariable = "Y";
       inputVariables = new List<string>() { "X" };
-      trainingPartition = new IntRange(0, 250);
-      testPartition = new IntRange(250, 500);
+      trainingPartition = new IntRange(0, 20);
+      testPartition = new IntRange(250, 350);
     }
 
@@ -54 +54 @@
       List<List<double>> dataList = new List<List<double>>();
       DoubleRange range = new DoubleRange(0, 4);
-      dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(testPartition.End, range));
+      dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(500, range));
 
       return dataList;

branches/RegressionBenchmarks/HeuristicLab.Problems.DataAnalysis.Benchmarks/3.4/RegressionBenchmarks/Nguyen/NguyenFunctionEleven.cs

@@ -37 +37 @@
       targetVariable = "Z";
       inputVariables = new List<string>() { "X", "Y" };
-      trainingPartition = new IntRange(0, 250);
-      testPartition = new IntRange(250, 500);
+      trainingPartition = new IntRange(0, 100);
+      testPartition = new IntRange(500, 1000);
     }
 
@@ -55 +55 @@
       List<List<double>> dataList = new List<List<double>>();
       DoubleRange range = new DoubleRange(0, 1);
-      dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(testPartition.End, range));
-      dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(testPartition.End, range));
+      dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(1000, range));
+      dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(1000, range));
 
       return dataList;

branches/RegressionBenchmarks/HeuristicLab.Problems.DataAnalysis.Benchmarks/3.4/RegressionBenchmarks/Nguyen/NguyenFunctionFive.cs

@@ -37 +37 @@
       targetVariable = "Y";
       inputVariables = new List<string>() { "X" };
-      trainingPartition = new IntRange(0, 250);
-      testPartition = new IntRange(250, 500);
+      trainingPartition = new IntRange(0, 20);
+      testPartition = new IntRange(250, 350);
     }
 
@@ -54 +54 @@
       List<List<double>> dataList = new List<List<double>>();
       DoubleRange range = new DoubleRange(-1, 1);
-      dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(testPartition.End, range));
+      dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(500, range));
 
       return dataList;

branches/RegressionBenchmarks/HeuristicLab.Problems.DataAnalysis.Benchmarks/3.4/RegressionBenchmarks/Nguyen/NguyenFunctionFour.cs

@@ -37 +37 @@
       targetVariable = "Y";
       inputVariables = new List<string>() { "X" };
-      trainingPartition = new IntRange(0, 250);
-      testPartition = new IntRange(250, 500);
+      trainingPartition = new IntRange(0, 20);
+      testPartition = new IntRange(250, 350);
     }
 
@@ -54 +54 @@
       List<List<double>> dataList = new List<List<double>>();
       DoubleRange range = new DoubleRange(-1, 1);
-      dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(testPartition.End, range));
+      dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(500, range));
 
       return dataList;

branches/RegressionBenchmarks/HeuristicLab.Problems.DataAnalysis.Benchmarks/3.4/RegressionBenchmarks/Nguyen/NguyenFunctionNine.cs

@@ -37 +37 @@
       targetVariable = "Z";
       inputVariables = new List<string>() { "X", "Y" };
-      trainingPartition = new IntRange(0, 250);
-      testPartition = new IntRange(250, 500);
+      trainingPartition = new IntRange(0, 100);
+      testPartition = new IntRange(500, 1000);
     }
 
@@ -55 +55 @@
       List<List<double>> dataList = new List<List<double>>();
       DoubleRange range = new DoubleRange(0, 1);
-      dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(testPartition.End, range));
-      dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(testPartition.End, range));
+      dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(1000, range));
+      dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(1000, range));
 
       return dataList;

branches/RegressionBenchmarks/HeuristicLab.Problems.DataAnalysis.Benchmarks/3.4/RegressionBenchmarks/Nguyen/NguyenFunctionOne.cs

@@ -37 +37 @@
       targetVariable = "Y";
       inputVariables = new List<string>() { "X" };
-      trainingPartition = new IntRange(0, 250);
-      testPartition = new IntRange(250, 500);
+      trainingPartition = new IntRange(0, 20);
+      testPartition = new IntRange(250, 350);
     }
 
@@ -54 +54 @@
       List<List<double>> dataList = new List<List<double>>();
       DoubleRange range = new DoubleRange(-1, 1);
-      dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(testPartition.End, range));
+      dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(500, range));
 
       return dataList;

branches/RegressionBenchmarks/HeuristicLab.Problems.DataAnalysis.Benchmarks/3.4/RegressionBenchmarks/Nguyen/NguyenFunctionSeven.cs

@@ -37 +37 @@
       targetVariable = "Y";
       inputVariables = new List<string>() { "X" };
-      trainingPartition = new IntRange(0, 250);
-      testPartition = new IntRange(250, 500);
+      trainingPartition = new IntRange(0, 20);
+      testPartition = new IntRange(250, 350);
     }
 
@@ -54 +54 @@
       List<List<double>> dataList = new List<List<double>>();
       DoubleRange range = new DoubleRange(0, 2);
-      dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(testPartition.End, range));
+      dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(500, range));
 
       return dataList;

branches/RegressionBenchmarks/HeuristicLab.Problems.DataAnalysis.Benchmarks/3.4/RegressionBenchmarks/Nguyen/NguyenFunctionSix.cs

@@ -37 +37 @@
       targetVariable = "Y";
       inputVariables = new List<string>() { "X" };
-      trainingPartition = new IntRange(0, 250);
-      testPartition = new IntRange(250, 500);
+      trainingPartition = new IntRange(0, 20);
+      testPartition = new IntRange(250, 350);
     }
 
@@ -54 +54 @@
       List<List<double>> dataList = new List<List<double>>();
       DoubleRange range = new DoubleRange(1, -1);
-      dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(testPartition.End, range));
+      dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(500, range));
 
       return dataList;

branches/RegressionBenchmarks/HeuristicLab.Problems.DataAnalysis.Benchmarks/3.4/RegressionBenchmarks/Nguyen/NguyenFunctionTen.cs

@@ -37 +37 @@
       targetVariable = "Z";
       inputVariables = new List<string>() { "X", "Y" };
-      trainingPartition = new IntRange(0, 250);
-      testPartition = new IntRange(250, 500);
+      trainingPartition = new IntRange(0, 100);
+      testPartition = new IntRange(500, 1000);
     }
 
@@ -55 +55 @@
       List<List<double>> dataList = new List<List<double>>();
       DoubleRange range = new DoubleRange(0, 1);
-      dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(testPartition.End, range));
-      dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(testPartition.End, range));
+      dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(1000, range));
+      dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(1000, range));
 
       return dataList;

branches/RegressionBenchmarks/HeuristicLab.Problems.DataAnalysis.Benchmarks/3.4/RegressionBenchmarks/Nguyen/NguyenFunctionThree.cs

@@ -37 +37 @@
       targetVariable = "Y";
       inputVariables = new List<string>() { "X" };
-      trainingPartition = new IntRange(0, 250);
-      testPartition = new IntRange(250, 500);
+      trainingPartition = new IntRange(0, 20);
+      testPartition = new IntRange(250, 350);
     }
 
@@ -54 +54 @@
       List<List<double>> dataList = new List<List<double>>();
       DoubleRange range = new DoubleRange(-1, 1);
-      dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(testPartition.End, range));
+      dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(500, range));
 
       return dataList;

branches/RegressionBenchmarks/HeuristicLab.Problems.DataAnalysis.Benchmarks/3.4/RegressionBenchmarks/Nguyen/NguyenFunctionTwelve.cs

@@ -37 +37 @@
       targetVariable = "Z";
       inputVariables = new List<string>() { "X", "Y" };
-      trainingPartition = new IntRange(0, 250);
-      testPartition = new IntRange(250, 500);
+      trainingPartition = new IntRange(0, 100);
+      testPartition = new IntRange(500, 1000);
     }
 
@@ -55 +55 @@
       List<List<double>> dataList = new List<List<double>>();
       DoubleRange range = new DoubleRange(0, 1);
-      dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(testPartition.End, range));
-      dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(testPartition.End, range));
+      dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(1000, range));
+      dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(1000, range));
 
       return dataList;

branches/RegressionBenchmarks/HeuristicLab.Problems.DataAnalysis.Benchmarks/3.4/RegressionBenchmarks/Nguyen/NguyenFunctionTwo.cs

@@ -37 +37 @@
       targetVariable = "Y";
       inputVariables = new List<string>() { "X" };
-      trainingPartition = new IntRange(0, 250);
-      testPartition = new IntRange(250, 500);
+      trainingPartition = new IntRange(0, 20);
+      testPartition = new IntRange(250, 350);
     }
 
@@ -54 +54 @@
       List<List<double>> dataList = new List<List<double>>();
       DoubleRange range = new DoubleRange(-1, 1);
-      dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(testPartition.End, range));
+      dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(500, range));
 
       return dataList;

branches/RegressionBenchmarks/HeuristicLab.Problems.DataAnalysis.Benchmarks/3.4/RegressionBenchmarks/Vladislavleva/KotanchekFunction.cs

@@ -38 +38 @@
       inputVariables = new List<string>() { "X1", "X2" };
       trainingPartition = new IntRange(0, 100);
-      testPartition = new IntRange(100, 2125);
+      testPartition = new IntRange(1000, 3025);
     }
 
@@ -55 +55 @@
       List<List<double>> dataList = new List<List<double>>();
       DoubleRange trainingRange = new DoubleRange(0.3, 4);
-      for (int i = 0; i < InputVariable.Count; i++) {
-        dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(TrainingPartition.End, trainingRange));
-      }
 
       List<double> oneVariableTestData = RegressionBenchmark.GenerateSteps(new DoubleRange(-0.2, 4.2), 0.1);
@@ -63 +60 @@
       testData = RegressionBenchmark.GenerateAllCombinationsOfValuesInLists(testData);
       for (int i = 0; i < InputVariable.Count; i++) {
+        dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(1000, trainingRange));
         dataList[i].AddRange(testData[i]);
       }

branches/RegressionBenchmarks/HeuristicLab.Problems.DataAnalysis.Benchmarks/3.4/RegressionBenchmarks/Vladislavleva/RationalPolynomialThreeDimensional.cs

@@ -38 +38 @@
       inputVariables = new List<string>() { "X1", "X2", "X3" };
       trainingPartition = new IntRange(0, 300);
-      testPartition = new IntRange(300, 3000);
+      testPartition = new IntRange(1000, 3700);
     }
 
@@ -55 +55 @@
     protected override List<List<double>> GenerateInput() {
       List<List<double>> dataList = new List<List<double>>();
-      dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(300, new DoubleRange(0.05, 2)));
-      dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(300, new DoubleRange(1, 2)));
-      dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(300, new DoubleRange(0.05, 2)));
+      int amountOfPoints = 1000;
+      dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(amountOfPoints, new DoubleRange(0.05, 2)));
+      dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(amountOfPoints, new DoubleRange(1, 2)));
+      dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(amountOfPoints, new DoubleRange(0.05, 2)));
 
       List<List<double>> testData = new List<List<double>>() { 

branches/RegressionBenchmarks/HeuristicLab.Problems.DataAnalysis.Benchmarks/3.4/RegressionBenchmarks/Vladislavleva/RationalPolynomialTwoDimensional.cs

@@ -38 +38 @@
       inputVariables = new List<string>() { "X1", "X2" };
       trainingPartition = new IntRange(0, 50);
-      testPartition = new IntRange(50, 1207);
+      testPartition = new IntRange(1000, 2157);
     }
 
@@ -55 +55 @@
       List<List<double>> dataList = new List<List<double>>();
       DoubleRange trainingRange = new DoubleRange(0.05, 6.05);
-      for (int i = 0; i < InputVariable.Count; i++) {
-        dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(TrainingPartition.End, trainingRange));
-      }
 
       List<double> oneVariableTestData = RegressionBenchmark.GenerateSteps(new DoubleRange(-0.25, 6.35), 0.2);
@@ -64 +61 @@
       testData = RegressionBenchmark.GenerateAllCombinationsOfValuesInLists(testData);
       for (int i = 0; i < InputVariable.Count; i++) {
+        dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(1000, trainingRange));
         dataList[i].AddRange(testData[i]);
       }

branches/RegressionBenchmarks/HeuristicLab.Problems.DataAnalysis.Benchmarks/3.4/RegressionBenchmarks/Vladislavleva/SineCosineFunction.cs

@@ -38 +38 @@
       inputVariables = new List<string>() { "X1", "X2" };
       trainingPartition = new IntRange(0, 30);
-      testPartition = new IntRange(30, 991);
+      testPartition = new IntRange(500, 1461);
     }
 
@@ -55 +55 @@
       List<List<double>> dataList = new List<List<double>>();
       DoubleRange trainingRange = new DoubleRange(0.1, 5.9);
-      for (int i = 0; i < InputVariable.Count; i++) {
-        dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(30, trainingRange));
-      }
 
       List<double> oneVariableTestData = RegressionBenchmark.GenerateSteps(new DoubleRange(-0.05, 6.05), 0.02);
@@ -64 +61 @@
 
       for (int i = 0; i < InputVariable.Count; i++) {
+        dataList.Add(RegressionBenchmark.GenerateUniformDistributedValues(500, trainingRange));
         dataList[i].AddRange(testData[i]);
       }

branches/RegressionBenchmarks/HeuristicLab.Problems.DataAnalysis.Benchmarks/3.4/RegressionGenerator/RegressionBenchmark.cs

@@ -20 +20 @@
 #endregion
 
+using System;
 using System.Collections.Generic;
 using System.Linq;
@@ -62 +63 @@
 
     public static List<double> GenerateSteps(DoubleRange range, double stepWidth) {
-      return Enumerable.Range(0, (int)((range.End - range.Start) / stepWidth) + 1)
+      return Enumerable.Range(0, (int)Math.Round(((range.End - range.Start) / stepWidth) + 1))
                                       .Select(i => (range.Start + i * stepWidth))
                                       .ToList<double>();