source: branches/MemPRAlgorithm/HeuristicLab.Algorithms.MemPR/3.3/LinearLinkage/SolutionModel/Univariate/UnbiasedModelTrainer.cs @ 14544

Last change on this file since 14544 was 14544, checked in by abeham, 3 years ago

#2701:

  • LLE: Added equality comparer
  • MemPR:
    • Added GPR to learn about heuristic performance
    • Changed Breeding to do more exhaustive search on crossover
    • Added Delinking separately to Relinking
    • Rewrote d/relinking for LLE
    • Reduce usage of local search
    • Renamed TabuWalk to AdaptiveWalk
    • Rewrote adaptive walk for binary problems
    • Renamed LLE namespace to Grouping to avoid namespace clashes
File size: 2.2 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 HeuristicLab.Algorithms.MemPR.Interfaces;
24using HeuristicLab.Common;
25using HeuristicLab.Core;
26using HeuristicLab.Encodings.LinearLinkageEncoding;
27using HeuristicLab.Optimization;
28using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
29
30namespace HeuristicLab.Algorithms.MemPR.Grouping.SolutionModel.Univariate {
31  [Item("Unbiased Univariate Model Trainer (linear linkage)", "", ExcludeGenericTypeInfo = true)]
32  [StorableClass]
33  public class UniasedModelTrainer<TContext> : NamedItem, ISolutionModelTrainer<TContext>
34    where TContext : IPopulationBasedHeuristicAlgorithmContext<SingleObjectiveBasicProblem<LinearLinkageEncoding>, LinearLinkage>, ISolutionModelContext<LinearLinkage> {
35   
36    [StorableConstructor]
37    protected UniasedModelTrainer(bool deserializing) : base(deserializing) { }
38    protected UniasedModelTrainer(UniasedModelTrainer<TContext> original, Cloner cloner) : base(original, cloner) { }
39    public UniasedModelTrainer() {
40      Name = ItemName;
41      Description = ItemDescription;
42    }
43
44    public override IDeepCloneable Clone(Cloner cloner) {
45      return new UniasedModelTrainer<TContext>(this, cloner);
46    }
47
48    public void TrainModel(TContext context) {
49      context.Model = Trainer.Train(context.Random, context.Population.Select(x => x.Solution));
50    }
51  }
52}
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