Changeset 9112 for branches/HeuristicLab.Problems.GaussianProcessTuning/HeuristicLab.Problems.Instances.DataAnalysis.GaussianProcessRegression/GaussianProcessSEIsoDependentNoise.cs

Timestamp:

01/04/13 22:34:57 (12 years ago)

Author:

gkronber

Message:

#1967: worked on tuned GP model and benchmark instances

File:

• branches/HeuristicLab.Problems.GaussianProcessTuning/HeuristicLab.Problems.Instances.DataAnalysis.GaussianProcessRegression/GaussianProcessSEIsoDependentNoise.cs (modified) (3 diffs)

branches/HeuristicLab.Problems.GaussianProcessTuning/HeuristicLab.Problems.Instances.DataAnalysis.GaussianProcessRegression/GaussianProcessSEIsoDependentNoise.cs

@@ -41 +41 @@
     protected override string[] AllowedInputVariables { get { return new string[] { "X1" }; } }
     protected override int TrainingPartitionStart { get { return 0; } }
-    protected override int TrainingPartitionEnd { get { return 100; } }
-    protected override int TestPartitionStart { get { return 100; } }
-    protected override int TestPartitionEnd { get { return 200; } }
+    protected override int TrainingPartitionEnd { get { return 250; } }
+    protected override int TestPartitionStart { get { return 250; } }
+    protected override int TestPartitionEnd { get { return 500; } }
 
     protected override List<List<double>> GenerateValues() {
@@ -56 +56 @@
       covarianceFunction.Terms.Add(new CovarianceSquaredExponentialIso());
       var prod = new CovarianceProduct();
-      prod.Factors.Add(new CovarianceSquaredExponentialIso());
+      prod.Factors.Add(new CovarianceLinear());
       prod.Factors.Add(new CovarianceNoise());
       covarianceFunction.Terms.Add(prod);
@@ -63 +63 @@
         {
           Math.Log(0.1), Math.Log(Math.Sqrt(1)), // SE iso
-          Math.Log(0.5), Math.Log(Math.Sqrt(1)), // SE iso for noise
-          Math.Log(Math.Sqrt(0.1)), // dependent noise
+          Math.Log(Math.Sqrt(0.5)), // dependent noise
           Math.Log(Math.Sqrt(0.01)) // noise
         };
-      var cov = covarianceFunction.GetParameterizedCovarianceFunction(hyp, Enumerable.Range(0, AllowedInputVariables.Count()));
+      var cov = covarianceFunction.GetParameterizedCovarianceFunction(hyp, null);
 
       var mt = new MersenneTwister(31415);