source: branches/OptimizationNetworks/HeuristicLab.Networks.IntegratedOptimization.MachineLearning/OrchestratedBinaryProblem.cs @ 14625

Last change on this file since 14625 was 14625, checked in by mkommend, 4 years ago

#2205: Added network for integrated machine learning.

File size: 2.6 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2017 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.Threading;
23using HeuristicLab.Common;
24using HeuristicLab.Core;
25using HeuristicLab.Data;
26using HeuristicLab.Encodings.BinaryVectorEncoding;
27using HeuristicLab.Optimization;
28using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
29
30namespace HeuristicLab.Networks.IntegratedOptimization.MachineLearning {
31  [StorableClass]
32  public sealed class OrchestratedBinaryProblem : SingleObjectiveBasicProblem<BinaryVectorEncoding> {
33
34    [Storable]
35    private readonly bool maximization;
36    public override bool Maximization { get { return maximization; } }
37
38    [Storable]
39    public FeatureSelectionOrchestrator Orchestrator { get; private set; }
40
41    [StorableConstructor]
42    private OrchestratedBinaryProblem(bool deserializing) : base(deserializing) { }
43    private OrchestratedBinaryProblem(OrchestratedBinaryProblem original, Cloner cloner)
44      : base(original, cloner) {
45      this.maximization = original.maximization;
46      this.Orchestrator = cloner.Clone(original.Orchestrator);
47    }
48    public override IDeepCloneable Clone(Cloner cloner) {
49      return new OrchestratedBinaryProblem(this, cloner);
50    }
51
52    public OrchestratedBinaryProblem(FeatureSelectionOrchestrator orchestator, int binaryVectorLength, bool maximization)
53      : base() {
54      Orchestrator = orchestator;
55      Encoding.Length = binaryVectorLength;
56      this.maximization = maximization;
57    }
58
59    public override double Evaluate(Individual individual, IRandom random) {
60      var msg = Orchestrator.FeatureSelectionEvaluationPort.PrepareMessage();
61      msg["BinaryVector"] = individual.BinaryVector();
62      Orchestrator.FeatureSelectionEvaluationPort.ReceiveMessage(msg, new CancellationToken());
63      var quality = (DoubleValue)msg["Quality"];
64      return quality.Value;
65    }
66  }
67}
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