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source: branches/PerformanceComparison/HeuristicLab.OptimizationExpertSystem.Common/3.3/Recommenders/KNearestNeighborRecommender.cs @ 14778

Last change on this file since 14778 was 13878, checked in by abeham, 9 years ago

#2457: added standardization of features for recommendation and using log10 of the expected runtime for clustering

File size: 2.4 KB
RevLine 
[13774]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.Data;
[13791]25using HeuristicLab.Optimization;
[13774]26using HeuristicLab.Parameters;
27using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
[13791]28using System.Linq;
[13774]29
30namespace HeuristicLab.OptimizationExpertSystem.Common {
31  [Item("K-Nearest Neighbor Recommender", "")]
32  [StorableClass]
33  public sealed class KNearestNeighborRecommender : ParameterizedNamedItem, IAlgorithmInstanceRecommender {
[13787]34   
[13774]35    private IFixedValueParameter<IntValue> KParameter {
36      get { return (IFixedValueParameter<IntValue>)Parameters["K"]; }
37    }
38
39    [StorableConstructor]
40    private KNearestNeighborRecommender(bool deserializing) : base(deserializing) { }
[13791]41    private KNearestNeighborRecommender(KNearestNeighborRecommender original, Cloner cloner) : base(original, cloner) { }
[13787]42    public KNearestNeighborRecommender() {
[13791]43      Parameters.Add(new FixedValueParameter<IntValue>("K", "The number of nearest neighbors to consider.", new IntValue(3)));
[13774]44    }
45
46    public override IDeepCloneable Clone(Cloner cloner) {
47      return new KNearestNeighborRecommender(this, cloner);
48    }
49
[13791]50    public IRecommendationModel TrainModel(IRun[] problemInstances, KnowledgeCenter kc, string[] characteristics) {
[13878]51      var perfData = problemInstances.Select(pi => new { ProblemInstance = pi, Performance = kc.GetAlgorithmPerformanceLog10(pi) })
[13791]52                                     .ToDictionary(x => x.ProblemInstance, x => x.Performance);
53      return new KNearestNeighborModel(KParameter.Value.Value, perfData, characteristics);
[13774]54    }
55  }
56}
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