source: branches/2974_Constants_Optimization/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/MultiObjective/SymbolicRegressionMultiObjectiveValidationBestSolutionAnalyzer.cs @ 17193

Last change on this file since 17193 was 17193, checked in by mkommend, 6 weeks ago

#2974: Merged trunk changes into branch.

File size: 3.5 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 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.Parameters;
26using HEAL.Attic;
27
28namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression {
29  /// <summary>
30  /// An operator that analyzes the validation best symbolic regression solution for multi objective symbolic regression problems.
31  /// </summary>
32  [Item("SymbolicRegressionMultiObjectiveValidationBestSolutionAnalyzer", "An operator that analyzes the validation best symbolic regression solution for multi objective symbolic regression problems.")]
33  [StorableType("64084F75-38B9-4501-BF2D-BB342B49F732")]
34  public sealed class SymbolicRegressionMultiObjectiveValidationBestSolutionAnalyzer : SymbolicDataAnalysisMultiObjectiveValidationBestSolutionAnalyzer<ISymbolicRegressionSolution, ISymbolicRegressionMultiObjectiveEvaluator, IRegressionProblemData>,
35    ISymbolicDataAnalysisBoundedOperator {
36    private const string EstimationLimitsParameterName = "EstimationLimits";
37
38    #region parameter properties
39    public IValueLookupParameter<DoubleLimit> EstimationLimitsParameter {
40      get { return (IValueLookupParameter<DoubleLimit>)Parameters[EstimationLimitsParameterName]; }
41    }
42    #endregion
43
44    [StorableConstructor]
45    private SymbolicRegressionMultiObjectiveValidationBestSolutionAnalyzer(StorableConstructorFlag _) : base(_) { }
46    private SymbolicRegressionMultiObjectiveValidationBestSolutionAnalyzer(SymbolicRegressionMultiObjectiveValidationBestSolutionAnalyzer original, Cloner cloner) : base(original, cloner) { }
47    public SymbolicRegressionMultiObjectiveValidationBestSolutionAnalyzer()
48      : base() {
49      Parameters.Add(new ValueLookupParameter<DoubleLimit>(EstimationLimitsParameterName, "The lower and upper limit for the estimated values produced by the symbolic regression model."));
50    }
51    public override IDeepCloneable Clone(Cloner cloner) {
52      return new SymbolicRegressionMultiObjectiveValidationBestSolutionAnalyzer(this, cloner);
53    }
54
55    protected override ISymbolicRegressionSolution CreateSolution(ISymbolicExpressionTree bestTree, double[] bestQuality) {
56      var model = new SymbolicRegressionModel(ProblemDataParameter.ActualValue.TargetVariable, (ISymbolicExpressionTree)bestTree.Clone(), SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper);
57      if (ApplyLinearScalingParameter.ActualValue.Value) model.Scale(ProblemDataParameter.ActualValue);
58      return new SymbolicRegressionSolution(model, (IRegressionProblemData)ProblemDataParameter.ActualValue.Clone());
59    }
60  }
61}
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