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| 2 | #region License Information
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| 3 | /* HeuristicLab
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| 4 | * Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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| 5 | *
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| 6 | * This file is part of HeuristicLab.
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| 7 | *
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| 8 | * HeuristicLab is free software: you can redistribute it and/or modify
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| 9 | * it under the terms of the GNU General Public License as published by
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| 10 | * the Free Software Foundation, either version 3 of the License, or
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| 11 | * (at your option) any later version.
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| 12 | *
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| 13 | * HeuristicLab is distributed in the hope that it will be useful,
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| 14 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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| 15 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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| 16 | * GNU General Public License for more details.
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| 17 | *
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| 18 | * You should have received a copy of the GNU General Public License
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| 19 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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| 20 | */
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| 21 | #endregion
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| 22 |
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| 23 | using HEAL.Attic;
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| 24 | using HeuristicLab.Algorithms.GradientDescent;
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| 25 | using HeuristicLab.Common;
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| 26 | using HeuristicLab.Core;
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| 27 | using HeuristicLab.Data;
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| 28 | using HeuristicLab.Operators;
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| 29 | using HeuristicLab.Optimization;
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| 30 | using HeuristicLab.Parameters;
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| 31 | using HeuristicLab.Problems.DataAnalysis;
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| 32 | using System.Linq;
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| 33 |
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| 34 | namespace HeuristicLab.Algorithms.DataAnalysis {
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| 35 | /// <summary>
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| 36 | /// Base class for Gaussian process data analysis algorithms (regression and classification).
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| 37 | /// </summary>
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| 38 | [StorableType("A5070F15-8E44-44DC-92E1-000826E933D3")]
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| 39 | public abstract class GaussianProcessBase : EngineAlgorithm {
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| 40 | protected const string MeanFunctionParameterName = "MeanFunction";
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| 41 | protected const string CovarianceFunctionParameterName = "CovarianceFunction";
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| 42 | protected const string MinimizationIterationsParameterName = "Iterations";
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| 43 | protected const string ApproximateGradientsParameterName = "ApproximateGradients";
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| 44 | protected const string SeedParameterName = "Seed";
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| 45 | protected const string SetSeedRandomlyParameterName = "SetSeedRandomly";
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| 46 | protected const string ModelCreatorParameterName = "GaussianProcessModelCreator";
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| 47 | protected const string NegativeLogLikelihoodParameterName = "NegativeLogLikelihood";
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| 48 | protected const string HyperparameterParameterName = "Hyperparameter";
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| 49 | protected const string HyperparameterGradientsParameterName = "HyperparameterGradients";
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| 50 | protected const string SolutionCreatorParameterName = "GaussianProcessSolutionCreator";
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| 51 | protected const string ScaleInputValuesParameterName = "ScaleInputValues";
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| 52 |
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| 53 | public new IDataAnalysisProblem Problem {
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| 54 | get { return (IDataAnalysisProblem)base.Problem; }
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| 55 | set { base.Problem = value; }
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| 56 | }
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| 57 |
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| 58 | #region parameter properties
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| 59 | public IValueParameter<IMeanFunction> MeanFunctionParameter {
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| 60 | get { return (IValueParameter<IMeanFunction>)Parameters[MeanFunctionParameterName]; }
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| 61 | }
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| 62 | public IValueParameter<ICovarianceFunction> CovarianceFunctionParameter {
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| 63 | get { return (IValueParameter<ICovarianceFunction>)Parameters[CovarianceFunctionParameterName]; }
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| 64 | }
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| 65 | public IValueParameter<IntValue> MinimizationIterationsParameter {
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| 66 | get { return (IValueParameter<IntValue>)Parameters[MinimizationIterationsParameterName]; }
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| 67 | }
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| 68 | public IValueParameter<IntValue> SeedParameter {
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| 69 | get { return (IValueParameter<IntValue>)Parameters[SeedParameterName]; }
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| 70 | }
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| 71 | public IValueParameter<BoolValue> SetSeedRandomlyParameter {
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| 72 | get { return (IValueParameter<BoolValue>)Parameters[SetSeedRandomlyParameterName]; }
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| 73 | }
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| 74 | public IFixedValueParameter<BoolValue> ScaleInputValuesParameter {
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| 75 | get { return (IFixedValueParameter<BoolValue>)Parameters[ScaleInputValuesParameterName]; }
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| 76 | }
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| 77 | #endregion
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| 78 | #region properties
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| 79 | public IMeanFunction MeanFunction {
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| 80 | set { MeanFunctionParameter.Value = value; }
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| 81 | get { return MeanFunctionParameter.Value; }
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| 82 | }
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| 83 | public ICovarianceFunction CovarianceFunction {
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| 84 | set { CovarianceFunctionParameter.Value = value; }
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| 85 | get { return CovarianceFunctionParameter.Value; }
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| 86 | }
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| 87 | public int MinimizationIterations {
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| 88 | set { MinimizationIterationsParameter.Value.Value = value; }
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| 89 | get { return MinimizationIterationsParameter.Value.Value; }
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| 90 | }
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| 91 | public int Seed { get { return SeedParameter.Value.Value; } set { SeedParameter.Value.Value = value; } }
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| 92 | public bool SetSeedRandomly { get { return SetSeedRandomlyParameter.Value.Value; } set { SetSeedRandomlyParameter.Value.Value = value; } }
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| 93 |
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| 94 | public bool ScaleInputValues {
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| 95 | get { return ScaleInputValuesParameter.Value.Value; }
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| 96 | set { ScaleInputValuesParameter.Value.Value = value; }
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| 97 | }
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| 98 | #endregion
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| 99 |
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| 100 | [StorableConstructor]
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| 101 | protected GaussianProcessBase(StorableConstructorFlag _) : base(_) { }
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| 102 | protected GaussianProcessBase(GaussianProcessBase original, Cloner cloner)
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| 103 | : base(original, cloner) {
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| 104 | }
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| 105 | protected GaussianProcessBase(IDataAnalysisProblem problem)
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| 106 | : base() {
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| 107 | Problem = problem;
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| 108 | Parameters.Add(new ValueParameter<IMeanFunction>(MeanFunctionParameterName, "The mean function to use.", new MeanConst()));
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| 109 | Parameters.Add(new ValueParameter<ICovarianceFunction>(CovarianceFunctionParameterName, "The covariance function to use.", new CovarianceSquaredExponentialIso()));
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| 110 | Parameters.Add(new ValueParameter<IntValue>(MinimizationIterationsParameterName, "The number of iterations for likelihood optimization with LM-BFGS.", new IntValue(20)));
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| 111 | Parameters.Add(new ValueParameter<IntValue>(SeedParameterName, "The random seed used to initialize the new pseudo random number generator.", new IntValue(0)));
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| 112 | Parameters.Add(new ValueParameter<BoolValue>(SetSeedRandomlyParameterName, "True if the random seed should be set to a random value, otherwise false.", new BoolValue(true)));
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| 113 |
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| 114 | Parameters.Add(new ValueParameter<BoolValue>(ApproximateGradientsParameterName, "Indicates that gradients should not be approximated (necessary for LM-BFGS).", new BoolValue(false)));
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| 115 | Parameters[ApproximateGradientsParameterName].Hidden = true; // should not be changed
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| 116 |
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| 117 | Parameters.Add(new FixedValueParameter<BoolValue>(ScaleInputValuesParameterName,
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| 118 | "Determines if the input variable values are scaled to the range [0..1] for training.", new BoolValue(true)));
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| 119 | Parameters[ScaleInputValuesParameterName].Hidden = true;
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| 120 |
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| 121 | // necessary for BFGS
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| 122 | Parameters.Add(new FixedValueParameter<BoolValue>("Maximization (BFGS)", new BoolValue(false)));
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| 123 | Parameters["Maximization (BFGS)"].Hidden = true;
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| 124 |
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| 125 | var randomCreator = new HeuristicLab.Random.RandomCreator();
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| 126 | var gpInitializer = new GaussianProcessHyperparameterInitializer();
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| 127 | var bfgsInitializer = new LbfgsInitializer();
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| 128 | var makeStep = new LbfgsMakeStep();
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| 129 | var branch = new ConditionalBranch();
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| 130 | var modelCreator = new Placeholder();
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| 131 | var updateResults = new LbfgsUpdateResults();
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| 132 | var analyzer = new LbfgsAnalyzer();
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| 133 | var finalModelCreator = new Placeholder();
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| 134 | var finalAnalyzer = new LbfgsAnalyzer();
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| 135 | var solutionCreator = new Placeholder();
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| 136 |
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| 137 | OperatorGraph.InitialOperator = randomCreator;
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| 138 | randomCreator.SeedParameter.ActualName = SeedParameterName;
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| 139 | randomCreator.SeedParameter.Value = null;
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| 140 | randomCreator.SetSeedRandomlyParameter.ActualName = SetSeedRandomlyParameterName;
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| 141 | randomCreator.SetSeedRandomlyParameter.Value = null;
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| 142 | randomCreator.Successor = gpInitializer;
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| 143 |
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| 144 | gpInitializer.CovarianceFunctionParameter.ActualName = CovarianceFunctionParameterName;
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| 145 | gpInitializer.MeanFunctionParameter.ActualName = MeanFunctionParameterName;
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| 146 | gpInitializer.ProblemDataParameter.ActualName = Problem.ProblemDataParameter.Name;
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| 147 | gpInitializer.HyperparameterParameter.ActualName = HyperparameterParameterName;
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| 148 | gpInitializer.RandomParameter.ActualName = randomCreator.RandomParameter.Name;
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| 149 | gpInitializer.Successor = bfgsInitializer;
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| 150 |
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| 151 | bfgsInitializer.IterationsParameter.ActualName = MinimizationIterationsParameterName;
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| 152 | bfgsInitializer.PointParameter.ActualName = HyperparameterParameterName;
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| 153 | bfgsInitializer.ApproximateGradientsParameter.ActualName = ApproximateGradientsParameterName;
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| 154 | bfgsInitializer.Successor = makeStep;
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| 155 |
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| 156 | makeStep.StateParameter.ActualName = bfgsInitializer.StateParameter.Name;
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| 157 | makeStep.PointParameter.ActualName = HyperparameterParameterName;
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| 158 | makeStep.Successor = branch;
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| 159 |
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| 160 | branch.ConditionParameter.ActualName = makeStep.TerminationCriterionParameter.Name;
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| 161 | branch.FalseBranch = modelCreator;
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| 162 | branch.TrueBranch = finalModelCreator;
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| 163 |
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| 164 | modelCreator.OperatorParameter.ActualName = ModelCreatorParameterName;
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| 165 | modelCreator.Successor = updateResults;
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| 166 |
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| 167 | updateResults.MaximizationParameter.ActualName = "Maximization (BFGS)";
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| 168 | updateResults.StateParameter.ActualName = bfgsInitializer.StateParameter.Name;
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| 169 | updateResults.QualityParameter.ActualName = NegativeLogLikelihoodParameterName;
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| 170 | updateResults.QualityGradientsParameter.ActualName = HyperparameterGradientsParameterName;
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| 171 | updateResults.ApproximateGradientsParameter.ActualName = ApproximateGradientsParameterName;
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| 172 | updateResults.Successor = analyzer;
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| 173 |
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| 174 | analyzer.QualityParameter.ActualName = NegativeLogLikelihoodParameterName;
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| 175 | analyzer.PointParameter.ActualName = HyperparameterParameterName;
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| 176 | analyzer.QualityGradientsParameter.ActualName = HyperparameterGradientsParameterName;
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| 177 | analyzer.StateParameter.ActualName = bfgsInitializer.StateParameter.Name;
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| 178 | analyzer.PointsTableParameter.ActualName = "Hyperparameter table";
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| 179 | analyzer.QualityGradientsTableParameter.ActualName = "Gradients table";
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| 180 | analyzer.QualitiesTableParameter.ActualName = "Negative log likelihood table";
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| 181 | analyzer.Successor = makeStep;
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| 182 |
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| 183 | finalModelCreator.OperatorParameter.ActualName = ModelCreatorParameterName;
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| 184 | finalModelCreator.Successor = finalAnalyzer;
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| 185 |
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| 186 | finalAnalyzer.QualityParameter.ActualName = NegativeLogLikelihoodParameterName;
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| 187 | finalAnalyzer.PointParameter.ActualName = HyperparameterParameterName;
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| 188 | finalAnalyzer.QualityGradientsParameter.ActualName = HyperparameterGradientsParameterName;
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| 189 | finalAnalyzer.PointsTableParameter.ActualName = analyzer.PointsTableParameter.ActualName;
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| 190 | finalAnalyzer.QualityGradientsTableParameter.ActualName = analyzer.QualityGradientsTableParameter.ActualName;
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| 191 | finalAnalyzer.QualitiesTableParameter.ActualName = analyzer.QualitiesTableParameter.ActualName;
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| 192 | finalAnalyzer.Successor = solutionCreator;
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| 193 |
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| 194 | solutionCreator.OperatorParameter.ActualName = SolutionCreatorParameterName;
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| 195 | }
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| 196 |
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| 197 | [StorableHook(HookType.AfterDeserialization)]
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| 198 | private void AfterDeserialization() {
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| 199 | // BackwardsCompatibility3.4
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| 200 | #region Backwards compatible code, remove with 3.5
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| 201 | if (Parameters.ContainsKey("Maximization")) {
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| 202 | Parameters.Remove("Maximization");
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| 203 | }
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| 204 |
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| 205 | if (!Parameters.ContainsKey("Maximization (BFGS)")) {
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| 206 | Parameters.Add(new FixedValueParameter<BoolValue>("Maximization (BFGS)", new BoolValue(false)));
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| 207 | Parameters["Maximization (BFGS)"].Hidden = true;
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| 208 | OperatorGraph.Operators.OfType<LbfgsUpdateResults>().First().MaximizationParameter.ActualName = "Maximization BFGS";
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| 209 | }
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| 210 |
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| 211 | if (!Parameters.ContainsKey(ScaleInputValuesParameterName)) {
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| 212 | Parameters.Add(new FixedValueParameter<BoolValue>(ScaleInputValuesParameterName,
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| 213 | "Determines if the input variable values are scaled to the range [0..1] for training.", new BoolValue(true)));
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| 214 | Parameters[ScaleInputValuesParameterName].Hidden = true;
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| 215 | }
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| 216 | #endregion
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| 217 | }
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| 218 | }
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| 219 | }
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