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source: branches/2457_ExpertSystem/HeuristicLab.OptimizationExpertSystem.Common/3.3/Recommenders/KNearestNeighborRecommender.cs @ 17328

Last change on this file since 17328 was 16958, checked in by abeham, 6 years ago

#2457: adapted to trunk

File size: 2.5 KB
Line 
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 System.Linq;
23using HEAL.Attic;
24using HeuristicLab.Common;
25using HeuristicLab.Core;
26using HeuristicLab.Data;
27using HeuristicLab.Optimization;
28using HeuristicLab.Parameters;
29
30namespace HeuristicLab.OptimizationExpertSystem.Common {
31  [Item("K-Nearest Neighbor Recommender", "")]
32  [StorableType("A2DB464F-3F1D-47B0-944B-DE252D461A0C")]
33  public sealed class KNearestNeighborRecommender : ParameterizedNamedItem, IAlgorithmInstanceRecommender {
34   
35    private IFixedValueParameter<IntValue> KParameter {
36      get { return (IFixedValueParameter<IntValue>)Parameters["K"]; }
37    }
38
39    public int K {
40      get { return KParameter.Value.Value; }
41      set { KParameter.Value.Value = value; }
42    }
43
44    [StorableConstructor]
45    private KNearestNeighborRecommender(StorableConstructorFlag _) : base(_) { }
46    private KNearestNeighborRecommender(KNearestNeighborRecommender original, Cloner cloner) : base(original, cloner) { }
47    public KNearestNeighborRecommender() {
48      Parameters.Add(new FixedValueParameter<IntValue>("K", "The number of nearest neighbors to consider.", new IntValue(3)));
49    }
50
51    public override IDeepCloneable Clone(Cloner cloner) {
52      return new KNearestNeighborRecommender(this, cloner);
53    }
54
55    public IRecommendationModel TrainModel(IRun[] problemInstances, KnowledgeCenter kc, string[] characteristics) {
56      var perfData = problemInstances.Select(pi => new { ProblemInstance = pi, Performance = kc.GetAlgorithmPerformanceLog10(pi) })
57                                     .ToDictionary(x => x.ProblemInstance, x => x.Performance);
58      return new KNearestNeighborModel(KParameter.Value.Value, perfData, characteristics);
59    }
60  }
61}
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