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source: branches/2971_named_intervals/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveValidationBestSolutionAnalyzer.cs @ 16641

Last change on this file since 16641 was 16641, checked in by gkronber, 5 years ago

#2971: merged r16527:16625 from trunk/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression to branch/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression (resolving all conflicts)

File size: 3.5 KB
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[5607]1#region License Information
2/* HeuristicLab
[16641]3 * Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
[5607]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.Parameters;
[16628]26using HEAL.Attic;
[16641]27using HEAL.Attic;
[5607]28
29namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression {
30  /// <summary>
31  /// An operator that analyzes the validation best symbolic regression solution for single objective symbolic regression problems.
32  /// </summary>
33  [Item("SymbolicRegressionSingleObjectiveValidationBestSolutionAnalyzer", "An operator that analyzes the validation best symbolic regression solution for single objective symbolic regression problems.")]
[16641]34  [StorableType("75E2AFFF-95B2-4FA4-8544-CF2025B65820")]
[5720]35  public sealed class SymbolicRegressionSingleObjectiveValidationBestSolutionAnalyzer : SymbolicDataAnalysisSingleObjectiveValidationBestSolutionAnalyzer<ISymbolicRegressionSolution, ISymbolicRegressionSingleObjectiveEvaluator, IRegressionProblemData>,
36    ISymbolicDataAnalysisBoundedOperator {
[5770]37    private const string EstimationLimitsParameterName = "EstimationLimits";
38
[5720]39    #region parameter properties
[5770]40    public IValueLookupParameter<DoubleLimit> EstimationLimitsParameter {
41      get { return (IValueLookupParameter<DoubleLimit>)Parameters[EstimationLimitsParameterName]; }
[5720]42    }
43    #endregion
44
[5607]45    [StorableConstructor]
[16628]46    private SymbolicRegressionSingleObjectiveValidationBestSolutionAnalyzer(StorableConstructorFlag _) : base(_) { }
[5607]47    private SymbolicRegressionSingleObjectiveValidationBestSolutionAnalyzer(SymbolicRegressionSingleObjectiveValidationBestSolutionAnalyzer original, Cloner cloner) : base(original, cloner) { }
48    public SymbolicRegressionSingleObjectiveValidationBestSolutionAnalyzer()
49      : base() {
[5770]50      Parameters.Add(new ValueLookupParameter<DoubleLimit>(EstimationLimitsParameterName, "The lower and upper limit for the estimated values produced by the symbolic regression model."));
[5607]51    }
[5720]52
[5607]53    public override IDeepCloneable Clone(Cloner cloner) {
54      return new SymbolicRegressionSingleObjectiveValidationBestSolutionAnalyzer(this, cloner);
55    }
56
57    protected override ISymbolicRegressionSolution CreateSolution(ISymbolicExpressionTree bestTree, double bestQuality) {
[13941]58      var model = new SymbolicRegressionModel(ProblemDataParameter.ActualValue.TargetVariable, (ISymbolicExpressionTree)bestTree.Clone(), SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper);
[8972]59      if (ApplyLinearScalingParameter.ActualValue.Value) model.Scale(ProblemDataParameter.ActualValue);
[5914]60      return new SymbolicRegressionSolution(model, (IRegressionProblemData)ProblemDataParameter.ActualValue.Clone());
[5607]61    }
62  }
63}
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