source: trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Regression/RegressionSolution.cs @ 12012

Last change on this file since 12012 was 12012, checked in by ascheibe, 5 years ago

#2212 merged r12008, r12009, r12010 back into trunk

File size: 3.1 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2015 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.Persistence.Default.CompositeSerializers.Storable;
26
27namespace HeuristicLab.Problems.DataAnalysis {
28  /// <summary>
29  /// Represents a regression data analysis solution
30  /// </summary>
31  [StorableClass]
32  public abstract class RegressionSolution : RegressionSolutionBase {
33    protected readonly Dictionary<int, double> evaluationCache;
34
35    [StorableConstructor]
36    protected RegressionSolution(bool deserializing)
37      : base(deserializing) {
38      evaluationCache = new Dictionary<int, double>();
39    }
40    protected RegressionSolution(RegressionSolution original, Cloner cloner)
41      : base(original, cloner) {
42      evaluationCache = new Dictionary<int, double>(original.evaluationCache);
43    }
44    protected RegressionSolution(IRegressionModel model, IRegressionProblemData problemData)
45      : base(model, problemData) {
46      evaluationCache = new Dictionary<int, double>(problemData.Dataset.Rows);
47      CalculateRegressionResults();
48    }
49
50
51    public override IEnumerable<double> EstimatedValues {
52      get { return GetEstimatedValues(Enumerable.Range(0, ProblemData.Dataset.Rows)); }
53    }
54    public override IEnumerable<double> EstimatedTrainingValues {
55      get { return GetEstimatedValues(ProblemData.TrainingIndices); }
56    }
57    public override IEnumerable<double> EstimatedTestValues {
58      get { return GetEstimatedValues(ProblemData.TestIndices); }
59    }
60
61    public override IEnumerable<double> GetEstimatedValues(IEnumerable<int> rows) {
62      var rowsToEvaluate = rows.Except(evaluationCache.Keys);
63      var rowsEnumerator = rowsToEvaluate.GetEnumerator();
64      var valuesEnumerator = Model.GetEstimatedValues(ProblemData.Dataset, rowsToEvaluate).GetEnumerator();
65
66      while (rowsEnumerator.MoveNext() & valuesEnumerator.MoveNext()) {
67        evaluationCache.Add(rowsEnumerator.Current, valuesEnumerator.Current);
68      }
69
70      return rows.Select(row => evaluationCache[row]);
71    }
72
73    protected override void OnProblemDataChanged() {
74      evaluationCache.Clear();
75      base.OnProblemDataChanged();
76    }
77
78    protected override void OnModelChanged() {
79      evaluationCache.Clear();
80      base.OnModelChanged();
81    }
82  }
83}
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