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source: branches/3044_variableScaling/HeuristicLab.Algorithms.DataAnalysis.DecisionTrees/3.4/Pruning/NoPruning.cs @ 17456

Last change on this file since 17456 was 17180, checked in by swagner, 5 years ago

#2875: Removed years in copyrights

File size: 1.9 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 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 System.Collections.Generic;
23using System.Threading;
24using HeuristicLab.Common;
25using HeuristicLab.Core;
26using HeuristicLab.Problems.DataAnalysis;
27using HEAL.Attic;
28
29namespace HeuristicLab.Algorithms.DataAnalysis {
30  [StorableType("D67152AA-3533-45D2-B77B-4A0742FB4B92")]
31  [Item("NoPruning", "No pruning")]
32  public sealed class NoPruning : ParameterizedNamedItem, IPruning {
33    #region Constructors & Cloning
34    [StorableConstructor]
35    private NoPruning(StorableConstructorFlag _) : base(_) { }
36    private NoPruning(NoPruning original, Cloner cloner) : base(original, cloner) { }
37    public NoPruning() { }
38    public override IDeepCloneable Clone(Cloner cloner) {
39      return new NoPruning(this, cloner);
40    }
41    #endregion
42
43
44    public int MinLeafSize(IRegressionProblemData pd, ILeafModel leafModel) {
45      return 0;
46    }
47    public void Initialize(IScope states) { }
48
49    public void Prune(RegressionNodeTreeModel treeModel, IReadOnlyList<int> trainingRows, IReadOnlyList<int> pruningRows, IScope scope, CancellationToken cancellationToken) { }
50  }
51}
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