[8623] | 1 |
|
---|
| 2 | #region License Information
|
---|
| 3 | /* HeuristicLab
|
---|
[12009] | 4 | * Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
|
---|
[8623] | 5 | *
|
---|
| 6 | * This file is part of HeuristicLab.
|
---|
| 7 | *
|
---|
| 8 | * HeuristicLab is free software: you can redistribute it and/or modify
|
---|
| 9 | * it under the terms of the GNU General Public License as published by
|
---|
| 10 | * the Free Software Foundation, either version 3 of the License, or
|
---|
| 11 | * (at your option) any later version.
|
---|
| 12 | *
|
---|
| 13 | * HeuristicLab is distributed in the hope that it will be useful,
|
---|
| 14 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
|
---|
| 15 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
---|
| 16 | * GNU General Public License for more details.
|
---|
| 17 | *
|
---|
| 18 | * You should have received a copy of the GNU General Public License
|
---|
| 19 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
|
---|
| 20 | */
|
---|
| 21 | #endregion
|
---|
| 22 |
|
---|
| 23 | using System;
|
---|
[9096] | 24 | using System.Linq;
|
---|
[8623] | 25 | using HeuristicLab.Algorithms.GradientDescent;
|
---|
| 26 | using HeuristicLab.Common;
|
---|
| 27 | using HeuristicLab.Core;
|
---|
| 28 | using HeuristicLab.Data;
|
---|
| 29 | using HeuristicLab.Operators;
|
---|
| 30 | using HeuristicLab.Optimization;
|
---|
| 31 | using HeuristicLab.Parameters;
|
---|
| 32 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
|
---|
[9096] | 33 | using HeuristicLab.PluginInfrastructure;
|
---|
[8623] | 34 | using HeuristicLab.Problems.DataAnalysis;
|
---|
| 35 |
|
---|
| 36 | namespace HeuristicLab.Algorithms.DataAnalysis {
|
---|
| 37 | /// <summary>
|
---|
| 38 | /// Gaussian process least-squares classification data analysis algorithm.
|
---|
| 39 | /// </summary>
|
---|
| 40 | [Item("Gaussian Process Least-Squares Classification", "Gaussian process least-squares classification data analysis algorithm.")]
|
---|
| 41 | [Creatable("Data Analysis")]
|
---|
| 42 | [StorableClass]
|
---|
[9096] | 43 | public sealed class GaussianProcessClassification : GaussianProcessBase, IStorableContent {
|
---|
[8623] | 44 | public string Filename { get; set; }
|
---|
| 45 |
|
---|
| 46 | public override Type ProblemType { get { return typeof(IClassificationProblem); } }
|
---|
| 47 | public new IClassificationProblem Problem {
|
---|
| 48 | get { return (IClassificationProblem)base.Problem; }
|
---|
| 49 | set { base.Problem = value; }
|
---|
| 50 | }
|
---|
| 51 |
|
---|
[9096] | 52 | private const string ModelParameterName = "Model";
|
---|
[8623] | 53 |
|
---|
| 54 | #region parameter properties
|
---|
[9098] | 55 | public IConstrainedValueParameter<IGaussianProcessClassificationModelCreator> GaussianProcessModelCreatorParameter {
|
---|
[9096] | 56 | get { return (IConstrainedValueParameter<IGaussianProcessClassificationModelCreator>)Parameters[ModelCreatorParameterName]; }
|
---|
[8623] | 57 | }
|
---|
[9098] | 58 | public IFixedValueParameter<GaussianProcessClassificationSolutionCreator> GaussianProcessSolutionCreatorParameter {
|
---|
[9096] | 59 | get { return (IFixedValueParameter<GaussianProcessClassificationSolutionCreator>)Parameters[SolutionCreatorParameterName]; }
|
---|
[8623] | 60 | }
|
---|
| 61 | #endregion
|
---|
| 62 |
|
---|
| 63 | [StorableConstructor]
|
---|
| 64 | private GaussianProcessClassification(bool deserializing) : base(deserializing) { }
|
---|
| 65 | private GaussianProcessClassification(GaussianProcessClassification original, Cloner cloner)
|
---|
| 66 | : base(original, cloner) {
|
---|
[9096] | 67 | RegisterEventHandlers();
|
---|
[8623] | 68 | }
|
---|
| 69 | public GaussianProcessClassification()
|
---|
[9096] | 70 | : base(new ClassificationProblem()) {
|
---|
[8623] | 71 | this.name = ItemName;
|
---|
| 72 | this.description = ItemDescription;
|
---|
| 73 |
|
---|
[9096] | 74 | var modelCreators = ApplicationManager.Manager.GetInstances<IGaussianProcessClassificationModelCreator>();
|
---|
| 75 | var defaultModelCreator = modelCreators.First(c => c is GaussianProcessClassificationModelCreator);
|
---|
[8623] | 76 |
|
---|
[9096] | 77 | // GP regression and classification algorithms only differ in the model and solution creators,
|
---|
| 78 | // thus we use a common base class and use operator parameters to implement the specific versions.
|
---|
| 79 | // Different model creators can be implemented,
|
---|
| 80 | // but the solution creator is implemented in a generic fashion already and we don't allow derived solution creators
|
---|
| 81 | Parameters.Add(new ConstrainedValueParameter<IGaussianProcessClassificationModelCreator>(ModelCreatorParameterName, "The operator to create the Gaussian process model.",
|
---|
| 82 | new ItemSet<IGaussianProcessClassificationModelCreator>(modelCreators), defaultModelCreator));
|
---|
| 83 | // this parameter is not intended to be changed,
|
---|
| 84 | Parameters.Add(new FixedValueParameter<GaussianProcessClassificationSolutionCreator>(SolutionCreatorParameterName, "The solution creator for the algorithm",
|
---|
| 85 | new GaussianProcessClassificationSolutionCreator()));
|
---|
| 86 | Parameters[SolutionCreatorParameterName].Hidden = true;
|
---|
[8623] | 87 |
|
---|
[9096] | 88 | ParameterizedModelCreators();
|
---|
[9098] | 89 | ParameterizeSolutionCreator(GaussianProcessSolutionCreatorParameter.Value);
|
---|
[9096] | 90 | RegisterEventHandlers();
|
---|
| 91 | }
|
---|
[8623] | 92 |
|
---|
| 93 |
|
---|
[9096] | 94 | [StorableHook(HookType.AfterDeserialization)]
|
---|
| 95 | private void AfterDeserialization() {
|
---|
| 96 | RegisterEventHandlers();
|
---|
| 97 | }
|
---|
[8623] | 98 |
|
---|
[9096] | 99 | public override IDeepCloneable Clone(Cloner cloner) {
|
---|
| 100 | return new GaussianProcessClassification(this, cloner);
|
---|
| 101 | }
|
---|
[8623] | 102 |
|
---|
[9096] | 103 | #region events
|
---|
| 104 | private void RegisterEventHandlers() {
|
---|
[9098] | 105 | GaussianProcessModelCreatorParameter.ValueChanged += ModelCreatorParameter_ValueChanged;
|
---|
[9096] | 106 | }
|
---|
[8623] | 107 |
|
---|
[9096] | 108 | private void ModelCreatorParameter_ValueChanged(object sender, EventArgs e) {
|
---|
[9098] | 109 | ParameterizedModelCreator(GaussianProcessModelCreatorParameter.Value);
|
---|
[9096] | 110 | }
|
---|
| 111 | #endregion
|
---|
[8623] | 112 |
|
---|
[9096] | 113 | private void ParameterizedModelCreators() {
|
---|
[9098] | 114 | foreach (var creator in GaussianProcessModelCreatorParameter.ValidValues) {
|
---|
[9096] | 115 | ParameterizedModelCreator(creator);
|
---|
| 116 | }
|
---|
| 117 | }
|
---|
[8623] | 118 |
|
---|
[9096] | 119 | private void ParameterizedModelCreator(IGaussianProcessClassificationModelCreator modelCreator) {
|
---|
[8623] | 120 | modelCreator.ProblemDataParameter.ActualName = Problem.ProblemDataParameter.Name;
|
---|
| 121 | modelCreator.MeanFunctionParameter.ActualName = MeanFunctionParameterName;
|
---|
| 122 | modelCreator.CovarianceFunctionParameter.ActualName = CovarianceFunctionParameterName;
|
---|
| 123 |
|
---|
[9096] | 124 | // parameter names fixed by the algorithm
|
---|
| 125 | modelCreator.ModelParameter.ActualName = ModelParameterName;
|
---|
| 126 | modelCreator.HyperparameterParameter.ActualName = HyperparameterParameterName;
|
---|
| 127 | modelCreator.HyperparameterGradientsParameter.ActualName = HyperparameterGradientsParameterName;
|
---|
| 128 | modelCreator.NegativeLogLikelihoodParameter.ActualName = NegativeLogLikelihoodParameterName;
|
---|
| 129 | }
|
---|
[8623] | 130 |
|
---|
[9096] | 131 | private void ParameterizeSolutionCreator(GaussianProcessClassificationSolutionCreator solutionCreator) {
|
---|
| 132 | solutionCreator.ModelParameter.ActualName = ModelParameterName;
|
---|
[8623] | 133 | solutionCreator.ProblemDataParameter.ActualName = Problem.ProblemDataParameter.Name;
|
---|
| 134 | }
|
---|
| 135 | }
|
---|
| 136 | }
|
---|