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Ignore:
Timestamp:
01/04/13 22:34:57 (12 years ago)
Author:
gkronber
Message:

#1967: worked on tuned GP model and benchmark instances

Location:
branches/HeuristicLab.Problems.GaussianProcessTuning/HeuristicLab.Problems.Instances.DataAnalysis.GaussianProcessRegression
Files:
1 added
12 edited

Legend:

Unmodified
Added
Removed

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

    r9099 r9112  
    4242    protected override string[] AllowedInputVariables { get { return new string[] { "X1", "X2", "X3", "X4", "X5", "X6", "X7", "X8", "X9", "X10" }; } }
    4343    protected override int TrainingPartitionStart { get { return 0; } }
    44     protected override int TrainingPartitionEnd { get { return 250; } }
    45     protected override int TestPartitionStart { get { return 250; } }
    46     protected override int TestPartitionEnd { get { return 500; } }
     44    protected override int TrainingPartitionEnd { get { return 500; } }
     45    protected override int TestPartitionStart { get { return 500; } }
     46    protected override int TestPartitionEnd { get { return 1000; } }
    4747
    4848    protected override List<List<double>> GenerateValues() {
    … …  
    129129      covarianceFunction.Terms.Add(t5);
    130130
    131       var cov = covarianceFunction.GetParameterizedCovarianceFunction(hyp, Enumerable.Range(0, AllowedInputVariables.Count()));
     131      var cov = covarianceFunction.GetParameterizedCovarianceFunction(hyp, null);
    132132
    133133

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

    r9099 r9112  
    5959        covarianceFunction.GetParameterizedCovarianceFunction(
    6060          new double[] { Math.Log(0.1), Math.Log(Math.Sqrt(1)), Math.Log(Math.Sqrt(0.01)) },
    61           Enumerable.Range(0, AllowedInputVariables.Count()));
     61          null);
    6262
    6363      var mt = new MersenneTwister(31415);

  • branches/HeuristicLab.Problems.GaussianProcessTuning/HeuristicLab.Problems.Instances.DataAnalysis.GaussianProcessRegression/GaussianProcessSEIso1.cs

    r9099 r9112  
    4141    protected override string[] AllowedInputVariables { get { return new string[] { "X1", "X2", "X3", "X4", "X5", "X6", "X7", "X8", "X9", "X10" }; } }
    4242    protected override int TrainingPartitionStart { get { return 0; } }
    43     protected override int TrainingPartitionEnd { get { return 50; } }
    44     protected override int TestPartitionStart { get { return 50; } }
    45     protected override int TestPartitionEnd { get { return 100; } }
     43    protected override int TrainingPartitionEnd { get { return 250; } }
     44    protected override int TestPartitionStart { get { return 250; } }
     45    protected override int TestPartitionEnd { get { return 500; } }
    4646
    4747    protected override List<List<double>> GenerateValues() {
    … …  
    6666      covFun.Terms.Add(new CovarianceNoise());
    6767
    68       var cov = covFun.GetParameterizedCovarianceFunction(hyp, Enumerable.Range(0, AllowedInputVariables.Count()));
     68      var cov = covFun.GetParameterizedCovarianceFunction(hyp, null);
    6969      var mt = new MersenneTwister();
    7070      var target = Util.SampleGaussianProcess(mt, cov, data);

  • branches/HeuristicLab.Problems.GaussianProcessTuning/HeuristicLab.Problems.Instances.DataAnalysis.GaussianProcessRegression/GaussianProcessSEIso2.cs

    r9099 r9112  
    4141    protected override string[] AllowedInputVariables { get { return new string[] { "X1", "X2", "X3", "X4", "X5", "X6", "X7", "X8", "X9", "X10" }; } }
    4242    protected override int TrainingPartitionStart { get { return 0; } }
    43     protected override int TrainingPartitionEnd { get { return 50; } }
    44     protected override int TestPartitionStart { get { return 50; } }
    45     protected override int TestPartitionEnd { get { return 100; } }
     43    protected override int TrainingPartitionEnd { get { return 250; } }
     44    protected override int TestPartitionStart { get { return 250; } }
     45    protected override int TestPartitionEnd { get { return 500; } }
    4646
    4747    protected override List<List<double>> GenerateValues() {
    … …  
    7070      covFun.Terms.Add(m2);
    7171      covFun.Terms.Add(new CovarianceNoise());
    72       var cov = covFun.GetParameterizedCovarianceFunction(hyp, Enumerable.Range(0, AllowedInputVariables.Count()));
     72      var cov = covFun.GetParameterizedCovarianceFunction(hyp, null);
    7373
    7474      var mt = new MersenneTwister();

  • branches/HeuristicLab.Problems.GaussianProcessTuning/HeuristicLab.Problems.Instances.DataAnalysis.GaussianProcessRegression/GaussianProcessSEIso3.cs

    r9099 r9112  
    4141    protected override string[] AllowedInputVariables { get { return new string[] { "X1", "X2", "X3", "X4", "X5", "X6", "X7", "X8", "X9", "X10" }; } }
    4242    protected override int TrainingPartitionStart { get { return 0; } }
    43     protected override int TrainingPartitionEnd { get { return 50; } }
    44     protected override int TestPartitionStart { get { return 50; } }
    45     protected override int TestPartitionEnd { get { return 100; } }
     43    protected override int TrainingPartitionEnd { get { return 250; } }
     44    protected override int TestPartitionStart { get { return 250; } }
     45    protected override int TestPartitionEnd { get { return 500; } }
    4646
    4747    protected override List<List<double>> GenerateValues() {
    … …  
    7575      covFun.Terms.Add(m3);
    7676      covFun.Terms.Add(new CovarianceNoise());
    77       var cov = covFun.GetParameterizedCovarianceFunction(hyp, Enumerable.Range(0, AllowedInputVariables.Count()));
     77      var cov = covFun.GetParameterizedCovarianceFunction(hyp, null);
    7878
    7979      var mt = new MersenneTwister();

  • branches/HeuristicLab.Problems.GaussianProcessTuning/HeuristicLab.Problems.Instances.DataAnalysis.GaussianProcessRegression/GaussianProcessSEIso4.cs

    r9099 r9112  
    4141    protected override string[] AllowedInputVariables { get { return new string[] { "X1", "X2", "X3", "X4", "X5", "X6", "X7", "X8", "X9", "X10" }; } }
    4242    protected override int TrainingPartitionStart { get { return 0; } }
    43     protected override int TrainingPartitionEnd { get { return 50; } }
    44     protected override int TestPartitionStart { get { return 50; } }
    45     protected override int TestPartitionEnd { get { return 100; } }
     43    protected override int TrainingPartitionEnd { get { return 250; } }
     44    protected override int TestPartitionStart { get { return 250; } }
     45    protected override int TestPartitionEnd { get { return 500; } }
    4646
    4747    protected override List<List<double>> GenerateValues() {
    … …  
    6666      covFun.Terms.Add(new CovarianceNoise());
    6767
    68       var cov = covFun.GetParameterizedCovarianceFunction(hyp, Enumerable.Range(0, AllowedInputVariables.Count()));
     68      var cov = covFun.GetParameterizedCovarianceFunction(hyp, null);
    6969      var mt = new MersenneTwister();
    7070      var target = Util.SampleGaussianProcess(mt, cov, data);

  • branches/HeuristicLab.Problems.GaussianProcessTuning/HeuristicLab.Problems.Instances.DataAnalysis.GaussianProcessRegression/GaussianProcessSEIso5.cs

    r9099 r9112  
    4141    protected override string[] AllowedInputVariables { get { return new string[] { "X1", "X2", "X3", "X4", "X5", "X6", "X7", "X8", "X9", "X10" }; } }
    4242    protected override int TrainingPartitionStart { get { return 0; } }
    43     protected override int TrainingPartitionEnd { get { return 50; } }
    44     protected override int TestPartitionStart { get { return 50; } }
    45     protected override int TestPartitionEnd { get { return 100; } }
     43    protected override int TrainingPartitionEnd { get { return 250; } }
     44    protected override int TestPartitionStart { get { return 250; } }
     45    protected override int TestPartitionEnd { get { return 500; } }
    4646
    4747    protected override List<List<double>> GenerateValues() {
    … …  
    6969      covFun.Terms.Add(m2);
    7070      covFun.Terms.Add(new CovarianceNoise());
    71       var cov = covFun.GetParameterizedCovarianceFunction(hyp, Enumerable.Range(0, AllowedInputVariables.Count()));
     71      var cov = covFun.GetParameterizedCovarianceFunction(hyp, null);
    7272
    7373      var mt = new MersenneTwister();

  • branches/HeuristicLab.Problems.GaussianProcessTuning/HeuristicLab.Problems.Instances.DataAnalysis.GaussianProcessRegression/GaussianProcessSEIso6.cs

    r9099 r9112  
    4141    protected override string[] AllowedInputVariables { get { return new string[] { "X1", "X2", "X3", "X4", "X5", "X6", "X7", "X8", "X9", "X10" }; } }
    4242    protected override int TrainingPartitionStart { get { return 0; } }
    43     protected override int TrainingPartitionEnd { get { return 50; } }
    44     protected override int TestPartitionStart { get { return 50; } }
    45     protected override int TestPartitionEnd { get { return 100; } }
     43    protected override int TrainingPartitionEnd { get { return 250; } }
     44    protected override int TestPartitionStart { get { return 250; } }
     45    protected override int TestPartitionEnd { get { return 500; } }
    4646
    4747    protected override List<List<double>> GenerateValues() {
    … …  
    8080      covFun.Terms.Add(m4);
    8181      covFun.Terms.Add(new CovarianceNoise());
    82       var cov = covFun.GetParameterizedCovarianceFunction(hyp, Enumerable.Range(0, AllowedInputVariables.Count()));
     82      var cov = covFun.GetParameterizedCovarianceFunction(hyp, null);
    8383
    8484

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

    r9099 r9112  
    4141    protected override string[] AllowedInputVariables { get { return new string[] { "X1" }; } }
    4242    protected override int TrainingPartitionStart { get { return 0; } }
    43     protected override int TrainingPartitionEnd { get { return 100; } }
    44     protected override int TestPartitionStart { get { return 100; } }
    45     protected override int TestPartitionEnd { get { return 200; } }
     43    protected override int TrainingPartitionEnd { get { return 250; } }
     44    protected override int TestPartitionStart { get { return 250; } }
     45    protected override int TestPartitionEnd { get { return 500; } }
    4646
    4747    protected override List<List<double>> GenerateValues() {
    … …  
    5656      covarianceFunction.Terms.Add(new CovarianceSquaredExponentialIso());
    5757      var prod = new CovarianceProduct();
    58       prod.Factors.Add(new CovarianceSquaredExponentialIso());
     58      prod.Factors.Add(new CovarianceLinear());
    5959      prod.Factors.Add(new CovarianceNoise());
    6060      covarianceFunction.Terms.Add(prod);
    … …  
    6363        {
    6464          Math.Log(0.1), Math.Log(Math.Sqrt(1)), // SE iso
    65           Math.Log(0.5), Math.Log(Math.Sqrt(1)), // SE iso for noise
    66           Math.Log(Math.Sqrt(0.1)), // dependent noise
     65          Math.Log(Math.Sqrt(0.5)), // dependent noise
    6766          Math.Log(Math.Sqrt(0.01)) // noise
    6867        };
    69       var cov = covarianceFunction.GetParameterizedCovarianceFunction(hyp, Enumerable.Range(0, AllowedInputVariables.Count()));
     68      var cov = covarianceFunction.GetParameterizedCovarianceFunction(hyp, null);
    7069
    7170      var mt = new MersenneTwister(31415);

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

    r9099 r9112  
    2626    <DebugType>pdbonly</DebugType>
    2727    <Optimize>true</Optimize>
    28     <OutputPath>..\..\bin\</OutputPath>
     28    <OutputPath>..\..\..\trunk\sources\bin\</OutputPath>
    2929    <DefineConstants>TRACE</DefineConstants>
    3030    <ErrorReport>prompt</ErrorReport>
    … …  
    5252  </PropertyGroup>
    5353  <PropertyGroup Condition="'$(Configuration)|$(Platform)' == 'Release|x86'">
    54     <OutputPath>..\..\bin\</OutputPath>
     54    <OutputPath>..\..\..\trunk\sources\bin\</OutputPath>
    5555    <DefineConstants>TRACE</DefineConstants>
    5656    <Optimize>true</Optimize>
    … …  
    8282  </PropertyGroup>
    8383  <PropertyGroup Condition="'$(Configuration)|$(Platform)' == 'Release|x64'">
    84     <OutputPath>..\..\bin\</OutputPath>
     84    <OutputPath>..\..\..\trunk\sources\bin\</OutputPath>
    8585    <DefineConstants>TRACE</DefineConstants>
    8686    <Optimize>true</Optimize>
    … …  
    178178  </ItemGroup>
    179179  <ItemGroup>
     180    <Compile Include="GaussianProcessRegressionInstance.cs" />
    180181    <Compile Include="GaussianProcessSEIso6.cs" />
    181182    <Compile Include="GaussianProcessSEIso1.cs" />

  • branches/HeuristicLab.Problems.GaussianProcessTuning/HeuristicLab.Problems.Instances.DataAnalysis.GaussianProcessRegression/Plugin.cs.frame

    r8879 r9112  
    2626  [PluginFile("HeuristicLab.Problems.Instances.DataAnalysis.GaussianProcessRegression-3.3.dll", PluginFileType.Assembly)]
    2727  [PluginDependency("HeuristicLab.ALGLIB", "3.6.0")]
    28   [PluginDependency("HeuristicLab.Algorithm.DataAnalysis", "3.4")]
     28  [PluginDependency("HeuristicLab.Algorithms.DataAnalysis", "3.4")]
    2929  [PluginDependency("HeuristicLab.Collections", "3.3")]
    3030  [PluginDependency("HeuristicLab.Common", "3.3")]

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

    r8879 r9112  
    2222using System;
    2323using System.Collections.Generic;
     24using HeuristicLab.Algorithms.DataAnalysis;
    2425
    2526namespace HeuristicLab.Problems.Instances.DataAnalysis {
    … …  
    4950      descriptorList.Add(new GaussianProcessPolyTen());
    5051      descriptorList.Add(new GaussianProcessSEIsoDependentNoise());
     52
     53      var covs = new ICovarianceFunction[] {
     54        new CovarianceSquaredExponentialIso(),
     55        new CovarianceSquaredExponentialArd(),
     56        new CovarianceLinear(),
     57        new CovarianceLinearArd(),
     58        new CovarianceMaternIso(),
     59        new CovariancePeriodic(),
     60        new CovarianceRationalQuadraticArd(),
     61        new CovarianceRationalQuadraticIso()
     62      };
     63      foreach (var cov in covs) {
     64        descriptorList.Add(new GaussianProcessRegressionInstance(cov));
     65      }
     66
    5167      return descriptorList;
    5268    }
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