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source: trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/ClassificationSolution.cs @ 6589

Last change on this file since 6589 was 6589, checked in by mkommend, 13 years ago

#1600: Adapted classification solutions to the same design as used by regression solutions.

File size: 2.2 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.Persistence.Default.CompositeSerializers.Storable;
26
27namespace HeuristicLab.Problems.DataAnalysis {
28  /// <summary>
29  /// Represents a classification data analysis solution
30  /// </summary>
31  [StorableClass]
32  public abstract class ClassificationSolution : ClassificationSolutionBase {
33    [StorableConstructor]
34    protected ClassificationSolution(bool deserializing) : base(deserializing) { }
35    protected ClassificationSolution(ClassificationSolution original, Cloner cloner)
36      : base(original, cloner) {
37    }
38    public ClassificationSolution(IClassificationModel model, IClassificationProblemData problemData)
39      : base(model, problemData) {
40    }
41
42    public override IEnumerable<double> EstimatedClassValues {
43      get { return GetEstimatedClassValues(Enumerable.Range(0, ProblemData.Dataset.Rows)); }
44    }
45    public override IEnumerable<double> EstimatedTrainingClassValues {
46      get { return GetEstimatedClassValues(ProblemData.TrainingIndizes); }
47    }
48    public override IEnumerable<double> EstimatedTestClassValues {
49      get { return GetEstimatedClassValues(ProblemData.TestIndizes); }
50    }
51
52    public override IEnumerable<double> GetEstimatedClassValues(IEnumerable<int> rows) {
53      return Model.GetEstimatedClassValues(ProblemData.Dataset, rows);
54    }
55  }
56}
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