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source: trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/NeuralNetwork/NeuralNetworkClassificationSolution.cs @ 12319

Last change on this file since 12319 was 12012, checked in by ascheibe, 10 years ago

#2212 merged r12008, r12009, r12010 back into trunk

File size: 2.2 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 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 neural network solution for a classification problem which can be visualized in the GUI.
30  /// </summary>
31  [Item("NeuralNetworkClassificationSolution", "Represents a neural network solution for a classification problem which can be visualized in the GUI.")]
32  [StorableClass]
33  public sealed class NeuralNetworkClassificationSolution : ClassificationSolution, INeuralNetworkClassificationSolution {
34
35    public new INeuralNetworkModel Model {
36      get { return (INeuralNetworkModel)base.Model; }
37      set { base.Model = value; }
38    }
39
40    [StorableConstructor]
41    private NeuralNetworkClassificationSolution(bool deserializing) : base(deserializing) { }
42    private NeuralNetworkClassificationSolution(NeuralNetworkClassificationSolution original, Cloner cloner)
43      : base(original, cloner) {
44    }
45    public NeuralNetworkClassificationSolution(IClassificationProblemData problemData, INeuralNetworkModel nnModel)
46      : base(nnModel, problemData) {
47    }
48
49    public override IDeepCloneable Clone(Cloner cloner) {
50      return new NeuralNetworkClassificationSolution(this, cloner);
51    }
52
53  }
54}
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