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source: branches/GP-MoveOperators/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/GaussianProcessDiscriminantFunctionClassificationModel.cs @ 9579

Last change on this file since 9579 was 8623, checked in by gkronber, 12 years ago

#1902 implemented LS Gaussian Process classification

File size: 2.6 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2012 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.Common;
23using HeuristicLab.Core;
24using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
25using HeuristicLab.Problems.DataAnalysis;
26
27namespace HeuristicLab.Algorithms.DataAnalysis {
28  /// <summary>
29  /// Represents a Gaussian process model.
30  /// </summary>
31  [StorableClass]
32  [Item("GaussianProcessDiscriminantFunctionClassificationModel",
33    "Represents a Gaussian process discriminant function classification model.")]
34  public sealed class GaussianProcessDiscriminantFunctionClassificationModel : DiscriminantFunctionClassificationModel {
35    [StorableConstructor]
36    private GaussianProcessDiscriminantFunctionClassificationModel(bool deserializing)
37      : base(deserializing) {
38    }
39
40    private GaussianProcessDiscriminantFunctionClassificationModel(
41      GaussianProcessDiscriminantFunctionClassificationModel original, Cloner cloner)
42      : base(original, cloner) {
43    }
44
45    public GaussianProcessDiscriminantFunctionClassificationModel(IGaussianProcessModel model, IDiscriminantFunctionThresholdCalculator thresholdCalculator)
46      : base(model, thresholdCalculator) {
47    }
48
49
50    public override IDeepCloneable Clone(Cloner cloner) {
51      return new GaussianProcessDiscriminantFunctionClassificationModel(this, cloner);
52    }
53
54
55    public override IDiscriminantFunctionClassificationSolution CreateDiscriminantFunctionClassificationSolution(IClassificationProblemData problemData) {
56      return new GaussianProcessDiscriminantFunctionClassificationSolution(this, problemData);
57    }
58
59    public override IClassificationSolution CreateClassificationSolution(IClassificationProblemData problemData) {
60      return CreateDiscriminantFunctionClassificationSolution(problemData);
61    }
62  }
63}
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