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source: trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/RandomForest/RandomForestRegressionSolution.cs @ 8837

Last change on this file since 8837 was 8837, checked in by gkronber, 11 years ago

#1964 removed call to RecalculateResults in the ctor of solutions derived from RegressionSolution

File size: 2.1 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 random forest solution for a regression problem which can be visualized in the GUI.
30  /// </summary>
31  [Item("RandomForestRegressionSolution", "Represents a random forest solution for a regression problem which can be visualized in the GUI.")]
32  [StorableClass]
33  public sealed class RandomForestRegressionSolution : RegressionSolution, IRandomForestRegressionSolution {
34
35    public new IRandomForestModel Model {
36      get { return (IRandomForestModel)base.Model; }
37      set { base.Model = value; }
38    }
39
40    [StorableConstructor]
41    private RandomForestRegressionSolution(bool deserializing) : base(deserializing) { }
42    private RandomForestRegressionSolution(RandomForestRegressionSolution original, Cloner cloner)
43      : base(original, cloner) {
44    }
45    public RandomForestRegressionSolution(IRegressionProblemData problemData, IRandomForestModel randomForestModel)
46      : base(randomForestModel, problemData) {
47    }
48
49    public override IDeepCloneable Clone(Cloner cloner) {
50      return new RandomForestRegressionSolution(this, cloner);
51    }
52  }
53}
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