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source: trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/RandomForest/RandomForestClassificationSolution.cs @ 14345

Last change on this file since 14345 was 14345, checked in by gkronber, 7 years ago

#2690: implemented methods to generate symbolic expression tree solutions for decision tree models (random forest and gradient boosted) as well as views which make it possible to inspect each of the individual trees in a GBT and RF solution

File size: 2.3 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2016 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 classification problem which can be visualized in the GUI.
30  /// </summary>
31  [Item("RandomForestClassificationSolution", "Represents a random forest solution for a classification problem which can be visualized in the GUI.")]
32  [StorableClass]
33  public sealed class RandomForestClassificationSolution : ClassificationSolution, IRandomForestClassificationSolution {
34
35    public new IRandomForestModel Model {
36      get { return (IRandomForestModel)base.Model; }
37      set { base.Model = value; }
38    }
39
40    public int NumberOfTrees {
41      get { return Model.NumberOfTrees; }
42    }
43
44    [StorableConstructor]
45    private RandomForestClassificationSolution(bool deserializing) : base(deserializing) { }
46    private RandomForestClassificationSolution(RandomForestClassificationSolution original, Cloner cloner)
47      : base(original, cloner) {
48    }
49    public RandomForestClassificationSolution(IRandomForestModel randomForestModel, IClassificationProblemData problemData)
50      : base(randomForestModel, problemData) {
51    }
52
53    public override IDeepCloneable Clone(Cloner cloner) {
54      return new RandomForestClassificationSolution(this, cloner);
55    }
56  }
57}
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