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source: branches/2971_named_intervals/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Regression/ConfidenceBoundRegressionSolution.cs @ 17210

Last change on this file since 17210 was 17210, checked in by gkronber, 5 years ago

#2971: merged r17180:17184 from trunk to branch

File size: 3.5 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 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 HEAL.Attic;
26
27namespace HeuristicLab.Problems.DataAnalysis {
28  /// <summary>
29  /// Represents a regression data analysis solution that supports confidence estimates
30  /// </summary>
31  [StorableType("C2D0DE07-E8F0-4850-AAF3-E2885EC1DDB6")]
32  public class ConfidenceRegressionSolution : RegressionSolution, IConfidenceRegressionSolution {
33    protected readonly Dictionary<int, double> varianceEvaluationCache;
34
35    public new IConfidenceRegressionModel Model {
36      get { return (IConfidenceRegressionModel)base.Model; }
37      set { base.Model = value; }
38    }
39
40    [StorableConstructor]
41    protected ConfidenceRegressionSolution(StorableConstructorFlag _) : base(_) {
42      varianceEvaluationCache = new Dictionary<int, double>();
43    }
44    protected ConfidenceRegressionSolution(ConfidenceRegressionSolution original, Cloner cloner)
45      : base(original, cloner) {
46      varianceEvaluationCache = new Dictionary<int, double>(original.varianceEvaluationCache);
47    }
48    public ConfidenceRegressionSolution(IConfidenceRegressionModel model, IRegressionProblemData problemData)
49      : base(model, problemData) {
50      varianceEvaluationCache = new Dictionary<int, double>(problemData.Dataset.Rows);
51    }
52
53    public override IDeepCloneable Clone(Cloner cloner) {
54      return new ConfidenceRegressionSolution(this, cloner);
55    }
56
57    public IEnumerable<double> EstimatedVariances {
58      get { return GetEstimatedVariances(Enumerable.Range(0, ProblemData.Dataset.Rows)); }
59    }
60    public IEnumerable<double> EstimatedTrainingVariances {
61      get { return GetEstimatedVariances(ProblemData.TrainingIndices); }
62    }
63    public IEnumerable<double> EstimatedTestVariances {
64      get { return GetEstimatedVariances(ProblemData.TestIndices); }
65    }
66
67    public IEnumerable<double> GetEstimatedVariances(IEnumerable<int> rows) {
68      var rowsToEvaluate = rows.Except(varianceEvaluationCache.Keys);
69      var rowsEnumerator = rowsToEvaluate.GetEnumerator();
70      var valuesEnumerator = Model.GetEstimatedVariances(ProblemData.Dataset, rowsToEvaluate).GetEnumerator();
71
72      while (rowsEnumerator.MoveNext() & valuesEnumerator.MoveNext()) {
73        varianceEvaluationCache.Add(rowsEnumerator.Current, valuesEnumerator.Current);
74      }
75
76      return rows.Select(row => varianceEvaluationCache[row]);
77    }
78
79    protected override void OnProblemDataChanged() {
80      varianceEvaluationCache.Clear();
81      base.OnProblemDataChanged();
82    }
83
84    protected override void OnModelChanged() {
85      varianceEvaluationCache.Clear();
86      base.OnModelChanged();
87    }
88  }
89}
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