source: trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveTrainingParetoBestSolutionAnalyzer.cs @ 15583

Last change on this file since 15583 was 15583, checked in by swagner, 3 years ago

#2640: Updated year of copyrights in license headers

File size: 2.9 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2018 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.Encodings.SymbolicExpressionTreeEncoding;
25using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
26
27namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression {
28  /// <summary>
29  /// An operator that collects the training Pareto-best symbolic regression solutions for single objective symbolic regression problems.
30  /// </summary>
31  [Item("SymbolicRegressionSingleObjectiveTrainingParetoBestSolutionAnalyzer", "An operator that collects the training Pareto-best symbolic regression solutions for single objective symbolic regression problems.")]
32  [StorableClass]
33  public sealed class SymbolicRegressionSingleObjectiveTrainingParetoBestSolutionAnalyzer : SymbolicDataAnalysisSingleObjectiveTrainingParetoBestSolutionAnalyzer<IRegressionProblemData, ISymbolicRegressionSolution> {
34
35    [StorableConstructor]
36    private SymbolicRegressionSingleObjectiveTrainingParetoBestSolutionAnalyzer(bool deserializing) : base(deserializing) { }
37    private SymbolicRegressionSingleObjectiveTrainingParetoBestSolutionAnalyzer(SymbolicRegressionSingleObjectiveTrainingParetoBestSolutionAnalyzer original, Cloner cloner) : base(original, cloner) { }
38    public SymbolicRegressionSingleObjectiveTrainingParetoBestSolutionAnalyzer() : base() { }
39    public override IDeepCloneable Clone(Cloner cloner) {
40      return new SymbolicRegressionSingleObjectiveTrainingParetoBestSolutionAnalyzer(this, cloner);
41    }
42
43    protected override ISymbolicRegressionSolution CreateSolution(ISymbolicExpressionTree bestTree) {
44      var model = new SymbolicRegressionModel(ProblemDataParameter.ActualValue.TargetVariable, (ISymbolicExpressionTree)bestTree.Clone(), SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper);
45      if (ApplyLinearScalingParameter.ActualValue.Value) model.Scale(ProblemDataParameter.ActualValue);
46      return new SymbolicRegressionSolution(model, (IRegressionProblemData)ProblemDataParameter.ActualValue.Clone());
47    }
48  }
49}
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