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source: branches/Persistence Test/HeuristicLab.GP.StructureIdentification.Classification/3.3/OffspringSelectionGPClassification.cs @ 3703

Last change on this file since 3703 was 2363, checked in by gkronber, 15 years ago

Fixed problems with classification algorithms. #746 (CEDMA server is not compatible with new data-modeling algorithms)

File size: 2.1 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2008 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 HeuristicLab.Core;
23using HeuristicLab.Modeling;
24using HeuristicLab.Operators;
25using HeuristicLab.Data;
26
27namespace HeuristicLab.GP.StructureIdentification.Classification {
28  public class OffspringSelectionGPClassification : HeuristicLab.GP.StructureIdentification.OffspringSelectionGPRegression, IClassificationAlgorithm {
29
30    public override string Name {
31      get {
32        return base.Name + " - Classification";
33      }
34    }
35
36    protected override IOperator CreateProblemInjector() {
37      return DefaultClassificationOperators.CreateProblemInjector();
38    }
39
40    protected override IOperator CreateModelAnalyzerOperator() {
41      return DefaultClassificationOperators.CreatePostProcessingOperator();
42    }
43
44    protected override IAnalyzerModel CreateGPModel() {
45      IScope bestModelScope = Engine.GlobalScope.SubScopes[0];
46      var model = new AnalyzerModel();
47
48      model.SetMetaData("SelectionPressure", bestModelScope.GetVariableValue<DoubleData>("SelectionPressure", false).Data);
49      DefaultStructureIdentificationOperators.PopulateAnalyzerModel(bestModelScope, model);
50      DefaultClassificationOperators.PopulateAnalyzerModel(bestModelScope, model);
51
52      return model;
53    }
54  }
55}
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