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# Changeset 9562

Ignore:
Timestamp:
05/31/13 17:20:17 (11 years ago)
Message:

#1967 worked on Gaussian process evolution.

Location:
branches/HeuristicLab.Problems.GaussianProcessTuning
Files:
11 edited

Unmodified
Removed
• ## branches/HeuristicLab.Problems.GaussianProcessTuning/HeuristicLab.Algorithms.DataAnalysis.Experimental/HeuristicLab.Algorithms.DataAnalysis.Experimental.csproj

 r9112 prompt4true Code Code {2e530a92-9788-4cb8-a754-a91092e770a3} HeuristicLab.Eigen {93b4a10e-8979-4028-8ccf-49d88d6fac0c}
• ## branches/HeuristicLab.Problems.GaussianProcessTuning/HeuristicLab.Algorithms.DataAnalysis.Experimental/TunedGaussianProcessModel.cs

 r9124 .ToArray(); var cov = covarianceFunction.GetParameterizedCovarianceFunction(covarianceParameter, null); var cov = covarianceFunction.GetParameterizedCovarianceFunction(covarianceParameter, Enumerable.Range(0, x.GetLength(1))); ILArray myL = ILMath.zeros(n, n); .Select(r => mean.Mean(newX, r)) .ToArray(); var cov = covarianceFunction.GetParameterizedCovarianceFunction(covarianceParameter, null); var cov = covarianceFunction.GetParameterizedCovarianceFunction(covarianceParameter, Enumerable.Range(0, x.GetLength(1))); for (int i = 0; i < newN; i++) { for (int j = 0; j < n; j++) { var kss = new double[newN]; ILArray sWKs = ILMath.zeros(n, newN); var cov = covarianceFunction.GetParameterizedCovarianceFunction(covarianceParameter, null); var cov = covarianceFunction.GetParameterizedCovarianceFunction(covarianceParameter, Enumerable.Range(0, x.GetLength(1))); // for stddev
• ## branches/HeuristicLab.Problems.GaussianProcessTuning/HeuristicLab.Problems.GaussianProcessTuning.Tests/GaussianProcessTuning.Tests.csproj

 r9112 prompt4true {6142B24E-9C86-410B-A65A-1DE65C8C2349} HeuristicLab.Algorithms.DataAnalysis.Experimental {2e530a92-9788-4cb8-a754-a91092e770a3} HeuristicLab.Eigen {9A04599C-D608-4240-8DA6-D41F51C515A3}
• ## branches/HeuristicLab.Problems.GaussianProcessTuning/HeuristicLab.Problems.GaussianProcessTuning.Tests/UnitTest.cs

 r9099 using HeuristicLab.Problems.DataAnalysis; using HeuristicLab.Random; using HeuristicLabEigen; using Microsoft.VisualStudio.TestTools.UnitTesting; } } */ */ } }

• ## branches/HeuristicLab.Problems.GaussianProcessTuning/HeuristicLab.Problems.GaussianProcessTuning/Evaluator.cs

 r8753 InterpreterParameter.ActualValue.EvaluateGaussianProcessConfiguration(tree, ProblemDataParameter.ActualValue, out quality, out solution); if (double.IsInfinity(quality) || double.IsNaN(quality)) quality = 1E6; // a large value QualityParameter.ActualValue = new DoubleValue(quality); if (solution != null)
• ## branches/HeuristicLab.Problems.GaussianProcessTuning/HeuristicLab.Problems.GaussianProcessTuning/GaussianProcessTuning.csproj

 r9338 {6142B24E-9C86-410B-A65A-1DE65C8C2349} HeuristicLab.Algorithms.DataAnalysis.Experimental
• ## branches/HeuristicLab.Problems.GaussianProcessTuning/HeuristicLab.Problems.GaussianProcessTuning/Grammar.cs

 r9387 var covRQiso = new CovRQIso(); var covNN = new CovNn(); var covPoly = new CovPoly(); var covPPoly = new CovPiecewisePoly(); var covMatern1 = new CovMatern(1); covMatern1.Name = "CovMatern1"; covMatern5, covNN, covPoly, covPPoly, covPeriodic, covPeriodic1, covMatern5, covNN, covPoly, covPPoly, covPeriodic, covPeriodic1,
• ## branches/HeuristicLab.Problems.GaussianProcessTuning/HeuristicLab.Problems.GaussianProcessTuning/Interpreter.cs

 r9387 gprAlg.GaussianProcessModelCreatorParameter.Value = gprAlg.GaussianProcessModelCreatorParameter.ValidValues.First( v => v is GaussianProcessRegressionModelCreator); v => v is EigenGaussianProcessRegressionModelCreator); gprAlg.MinimizationIterations = 50; } else if (node.Symbol is CovNn) { return new CovarianceNeuralNetwork(); } else if (node.Symbol is CovPoly) { return new CovariancePolynomial(); } else if (node.Symbol is CovPiecewisePoly) { return new CovariancePiecewisePolynomial(); } else if (node.Symbol is CovPeriodic) { return new CovariancePeriodic();
• ## branches/HeuristicLab.Problems.GaussianProcessTuning/HeuristicLab.Problems.GaussianProcessTuning/Symbols.cs

 r9387 } [StorableClass] public sealed class CovPoly : Symbol { public override int MinimumArity { get { return 0; } } public override int MaximumArity { get { return 0; } } [StorableConstructor] private CovPoly(bool deserializing) : base(deserializing) { } private CovPoly(CovPoly original, Cloner cloner) : base(original, cloner) { } public CovPoly() : base("CovPoly", "") { } [StorableHook(HookType.AfterDeserialization)] private void AfterDeserialization() { } public override ISymbolicExpressionTreeNode CreateTreeNode() { return new CovPolyTreeNode(this); } public override IDeepCloneable Clone(Cloner cloner) { return new CovPoly(this, cloner); } } [StorableClass] public sealed class CovPiecewisePoly : Symbol { public override int MinimumArity { get { return 0; } } public override int MaximumArity { get { return 0; } } [StorableConstructor] private CovPiecewisePoly(bool deserializing) : base(deserializing) { } private CovPiecewisePoly(CovPiecewisePoly original, Cloner cloner) : base(original, cloner) { } public CovPiecewisePoly() : base("CovPiecewisePoly", "") { } [StorableHook(HookType.AfterDeserialization)] private void AfterDeserialization() { } public override ISymbolicExpressionTreeNode CreateTreeNode() { return new CovPiecewisePolyTreeNode(this); } public override IDeepCloneable Clone(Cloner cloner) { return new CovPiecewisePoly(this, cloner); } } [StorableClass] public sealed class CovNn : Symbol { public override int MinimumArity {
• ## branches/HeuristicLab.Problems.GaussianProcessTuning/HeuristicLab.Problems.GaussianProcessTuning/TreeNodes.cs

 r9387 } [StorableClass] public sealed class CovPolyTreeNode : SymbolicExpressionTreeTerminalNode { public new CovPoly Symbol { get { return (CovPoly)base.Symbol; } } [StorableConstructor] private CovPolyTreeNode(bool deserializing) : base(deserializing) { } private CovPolyTreeNode(CovPolyTreeNode original, Cloner cloner) : base(original, cloner) { } public CovPolyTreeNode(CovPoly symbol) : base(symbol) { } [StorableHook(HookType.AfterDeserialization)] private void AfterDeserialization() { } public override IDeepCloneable Clone(Cloner cloner) { return new CovPolyTreeNode(this, cloner); } } [StorableClass] public sealed class CovPiecewisePolyTreeNode : SymbolicExpressionTreeTerminalNode { public new CovPiecewisePoly Symbol { get { return (CovPiecewisePoly)base.Symbol; } } [StorableConstructor] private CovPiecewisePolyTreeNode(bool deserializing) : base(deserializing) { } private CovPiecewisePolyTreeNode(CovPiecewisePolyTreeNode original, Cloner cloner) : base(original, cloner) { } public CovPiecewisePolyTreeNode(CovPiecewisePoly symbol) : base(symbol) { } [StorableHook(HookType.AfterDeserialization)] private void AfterDeserialization() { } public override IDeepCloneable Clone(Cloner cloner) { return new CovPiecewisePolyTreeNode(this, cloner); } } [StorableClass] public sealed class CovNnTreeNode : SymbolicExpressionTreeTerminalNode { public new CovNn Symbol { get { return (CovNn)base.Symbol; } }
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