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Timestamp:
03/31/13 13:17:49 (12 years ago)
Author:
gkronber
Message:

#1967: minor adaptations necessary for the EuroCAST presentation

Location:
branches/HeuristicLab.Problems.GaussianProcessTuning
Files:
1 added
3 edited

Legend:

Unmodified
Added
Removed

  • branches/HeuristicLab.Problems.GaussianProcessTuning

    • Property svn:ignore

      •  

        old new  
        44*.testsettings
        55*.user
         6bin

  • branches/HeuristicLab.Problems.GaussianProcessTuning/HeuristicLab.Problems.Instances.DataAnalysis.GaussianProcessRegression/Instances.DataAnalysis.GaussianProcessRegression-3.3.csproj

    r9214 r9338  
    178178  </ItemGroup>
    179179  <ItemGroup>
     180    <Compile Include="GaussianProcessRegressionDemo.cs" />
    180181    <Compile Include="GaussianProcess2dPeriodic.cs" />
    181182    <Compile Include="GaussianProcessRegressionInstance1D.cs" />

  • branches/HeuristicLab.Problems.GaussianProcessTuning/HeuristicLab.Problems.Instances.DataAnalysis.GaussianProcessRegression/VariousInstanceProvider.cs

    r9214 r9338  
    135135      {
    136136        var cov = new CovarianceSum();
     137        cov.Terms.Add(new CovarianceSquaredExponentialIso());
     138        cov.Terms.Add(new CovarianceNoise());
     139        var hyp = new double[] { -2.5, 0, -7 };
     140        descriptorList.Add(new GaussianProcessRegressionDemo("1D: SE Noise", cov, hyp));
     141      }
     142      {
     143        var cov = new CovarianceSum();
     144        cov.Terms.Add(new CovarianceRationalQuadraticIso());
     145        cov.Terms.Add(new CovarianceNoise());
     146        var hyp = new double[] { -2.5, 0, -1, -7 };
     147        descriptorList.Add(new GaussianProcessRegressionDemo("1D: RQ Noise", cov, hyp));
     148      }
     149      {
     150        var cov = new CovarianceSum();
     151        var t = new CovarianceMaternIso();
     152        t.DParameter.Value = t.DParameter.ValidValues.First(x => x.Value == 3);
     153        cov.Terms.Add(t);
     154        cov.Terms.Add(new CovarianceNoise());
     155        var hyp = new double[] { -1.5, 0, -7 };
     156        descriptorList.Add(new GaussianProcessRegressionDemo("1D: Matern3 Noise", cov, hyp));
     157      }
     158      {
     159        var cov = new CovarianceSum();
     160        var t = new CovariancePeriodic();
     161        t.PeriodParameter.Value = new DoubleValue(0.3);
     162        cov.Terms.Add(t);
     163        cov.Terms.Add(new CovarianceNoise());
     164        var hyp = new double[] { 0, 0, -7 };
     165        descriptorList.Add(new GaussianProcessRegressionDemo("1D: Periodic Noise", cov, hyp));
     166      }
     167      {
     168        var cov = new CovarianceSum();
    137169        cov.Terms.Add(new CovarianceRationalQuadraticIso());
    138170        cov.Terms.Add(new CovarianceNoise());
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