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source: branches/ClassificationEnsembleVoting/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Clustering/ClusteringProblem.cs @ 12865

Last change on this file since 12865 was 7866, checked in by sforsten, 12 years ago

#1776:

  • merged r7454:7863 trunk into branch to make it compatible again
  • adjusted GetConfidence of MajorityVoteWeightCalculator to be in an interval of [0, 1]
File size: 1.6 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;
25
26namespace HeuristicLab.Problems.DataAnalysis {
27  [StorableClass]
28  [Item("Clustering Problem", "A general clustering problem.")]
29  [Creatable("Problems")]
30  public class ClusteringProblem : DataAnalysisProblem<IClusteringProblemData>, IClusteringProblem {
31    [StorableConstructor]
32    protected ClusteringProblem(bool deserializing) : base(deserializing) { }
33    protected ClusteringProblem(ClusteringProblem original, Cloner cloner) : base(original, cloner) { }
34    public override IDeepCloneable Clone(Cloner cloner) { return new ClusteringProblem(this, cloner); }
35
36    public ClusteringProblem()
37      : base() {
38      ProblemData = new ClusteringProblemData();
39    }
40  }
41}
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