source: trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/ClassificationEnsembleModel.cs @ 6666

Last change on this file since 6666 was 6666, checked in by mkommend, 11 years ago

#1592: Enabled creation of empty ensemble solutions and problem data changes.

File size: 3.8 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2011 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;
27
28namespace HeuristicLab.Problems.DataAnalysis {
29  /// <summary>
30  /// Represents classification solutions that contain an ensemble of multiple classification models
31  /// </summary>
32  [StorableClass]
33  [Item("ClassificationEnsembleModel", "A classification model that contains an ensemble of multiple classification models")]
34  public class ClassificationEnsembleModel : NamedItem, IClassificationEnsembleModel {
35
36    [Storable]
37    private List<IClassificationModel> models;
38    public IEnumerable<IClassificationModel> Models {
39      get { return new List<IClassificationModel>(models); }
40    }
41
42    [StorableConstructor]
43    protected ClassificationEnsembleModel(bool deserializing) : base(deserializing) { }
44    protected ClassificationEnsembleModel(ClassificationEnsembleModel original, Cloner cloner)
45      : base(original, cloner) {
46      this.models = original.Models.Select(m => cloner.Clone(m)).ToList();
47    }
48
49    public ClassificationEnsembleModel() : this(Enumerable.Empty<IClassificationModel>()) { }
50    public ClassificationEnsembleModel(IEnumerable<IClassificationModel> models)
51      : base() {
52      this.name = ItemName;
53      this.description = ItemDescription;
54      this.models = new List<IClassificationModel>(models);
55    }
56
57    public override IDeepCloneable Clone(Cloner cloner) {
58      return new ClassificationEnsembleModel(this, cloner);
59    }
60
61    #region IClassificationEnsembleModel Members
62    public void Add(IClassificationModel model) {
63      models.Add(model);
64    }
65    public void Remove(IClassificationModel model) {
66      models.Remove(model);
67    }
68
69    public IEnumerable<IEnumerable<double>> GetEstimatedClassValueVectors(Dataset dataset, IEnumerable<int> rows) {
70      var estimatedValuesEnumerators = (from model in models
71                                        select model.GetEstimatedClassValues(dataset, rows).GetEnumerator())
72                                       .ToList();
73
74      while (estimatedValuesEnumerators.All(en => en.MoveNext())) {
75        yield return from enumerator in estimatedValuesEnumerators
76                     select enumerator.Current;
77      }
78    }
79
80    #endregion
81
82    #region IClassificationModel Members
83
84    public IEnumerable<double> GetEstimatedClassValues(Dataset dataset, IEnumerable<int> rows) {
85      foreach (var estimatedValuesVector in GetEstimatedClassValueVectors(dataset, rows)) {
86        // return the class which is most often occuring
87        yield return
88          estimatedValuesVector
89          .GroupBy(x => x)
90          .OrderBy(g => -g.Count())
91          .Select(g => g.Key)
92          .First();
93      }
94    }
95
96    IClassificationSolution IClassificationModel.CreateClassificationSolution(IClassificationProblemData problemData) {
97      return new ClassificationEnsembleSolution(models, problemData);
98    }
99    #endregion
100  }
101}
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