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source: trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/GaussianProcessRegressionSolution.cs @ 8732

Last change on this file since 8732 was 8732, checked in by gkronber, 11 years ago

#1902:

  • added caching for variances of GaussianProcessRegressionSolution.
  • changed hyperparameter initializers to generate initial values for hyperparameters in a larger range.
File size: 3.7 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2012 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
4 *
5 * This file is part of HeuristicLab.
6 *
7 * HeuristicLab is free software: you can redistribute it and/or modify
8 * it under the terms of the GNU General Public License as published by
9 * the Free Software Foundation, either version 3 of the License, or
10 * (at your option) any later version.
11 *
12 * HeuristicLab is distributed in the hope that it will be useful,
13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
15 * GNU General Public License for more details.
16 *
17 * You should have received a copy of the GNU General Public License
18 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
19 */
20#endregion
21
22using System.Collections.Generic;
23using System.Linq;
24using HeuristicLab.Common;
25using HeuristicLab.Core;
26using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
27using HeuristicLab.Problems.DataAnalysis;
28
29namespace HeuristicLab.Algorithms.DataAnalysis {
30  /// <summary>
31  /// Represents a Gaussian process solution for a regression problem which can be visualized in the GUI.
32  /// </summary>
33  [Item("GaussianProcessRegressionSolution", "Represents a Gaussian process solution for a regression problem which can be visualized in the GUI.")]
34  [StorableClass]
35  public sealed class GaussianProcessRegressionSolution : RegressionSolution, IGaussianProcessSolution {
36    private new readonly Dictionary<int, double> evaluationCache;
37
38    public new IGaussianProcessModel Model {
39      get { return (IGaussianProcessModel)base.Model; }
40      set { base.Model = value; }
41    }
42
43    [StorableConstructor]
44    private GaussianProcessRegressionSolution(bool deserializing)
45      : base(deserializing) {
46      evaluationCache = new Dictionary<int, double>();
47
48    }
49    private GaussianProcessRegressionSolution(GaussianProcessRegressionSolution original, Cloner cloner)
50      : base(original, cloner) {
51      evaluationCache = new Dictionary<int, double>(original.evaluationCache);
52    }
53    public GaussianProcessRegressionSolution(IGaussianProcessModel model, IRegressionProblemData problemData)
54      : base(model, problemData) {
55
56      evaluationCache = new Dictionary<int, double>(problemData.Dataset.Rows);
57      RecalculateResults();
58    }
59
60    public override IDeepCloneable Clone(Cloner cloner) {
61      return new GaussianProcessRegressionSolution(this, cloner);
62    }
63
64    public IEnumerable<double> EstimatedVariance {
65      get { return GetEstimatedVariance(Enumerable.Range(0, ProblemData.Dataset.Rows)); }
66    }
67    public IEnumerable<double> EstimatedTrainingVariance {
68      get { return GetEstimatedVariance(ProblemData.TrainingIndices); }
69    }
70    public IEnumerable<double> EstimatedTestVariance {
71      get { return GetEstimatedVariance(ProblemData.TestIndices); }
72    }
73
74    public IEnumerable<double> GetEstimatedVariance(IEnumerable<int> rows) {
75      var rowsToEvaluate = rows.Except(evaluationCache.Keys);
76      var rowsEnumerator = rowsToEvaluate.GetEnumerator();
77      var valuesEnumerator = Model.GetEstimatedVariance(ProblemData.Dataset, rowsToEvaluate).GetEnumerator();
78
79      while (rowsEnumerator.MoveNext() & valuesEnumerator.MoveNext()) {
80        evaluationCache.Add(rowsEnumerator.Current, valuesEnumerator.Current);
81      }
82
83      return rows.Select(row => evaluationCache[row]);
84    }
85
86    protected override void OnModelChanged() {
87      evaluationCache.Clear();
88      base.OnModelChanged();
89    }
90    protected override void OnProblemDataChanged() {
91      evaluationCache.Clear();
92      base.OnProblemDataChanged();
93    }
94  }
95}
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