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source: branches/ParameterBinding/HeuristicLab.Problems.DataAnalysis.Classification/3.3/Symbolic/Evaluators/SymbolicClassificationMeanSquaredErrorEvaluator.cs @ 6409

Last change on this file since 6409 was 4722, checked in by swagner, 14 years ago

Merged cloning refactoring branch back into trunk (#922)

File size: 2.0 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2010 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.Regression.Symbolic;
26
27namespace HeuristicLab.Problems.DataAnalysis.Classification {
28  [Item("SymbolicClassificationMeanSquaredErrorEvaluator", "Calculates the mean squared error of a symbolic classification solution.")]
29  [StorableClass]
30  public sealed class SymbolicClassifacitionMeanSquaredErrorEvaluator : SymbolicRegressionMeanSquaredErrorEvaluator, ISymbolicClassificationEvaluator {
31    public ClassificationProblemData ClassificationProblemData {
32      get { return (ClassificationProblemData)RegressionProblemData; }
33    }
34
35    [StorableConstructor]
36    private SymbolicClassifacitionMeanSquaredErrorEvaluator(bool deserializing) : base(deserializing) { }
37    private SymbolicClassifacitionMeanSquaredErrorEvaluator(SymbolicClassifacitionMeanSquaredErrorEvaluator original, Cloner cloner) : base(original, cloner) { }
38    public SymbolicClassifacitionMeanSquaredErrorEvaluator() : base() { }
39    public override IDeepCloneable Clone(Cloner cloner) {
40      return new SymbolicClassifacitionMeanSquaredErrorEvaluator(this, cloner);
41    }
42  }
43}
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