Free cookie consent management tool by TermsFeed Policy Generator

source: branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/MultiObjective/SymbolicRegressionMultiObjectiveValidationBestSolutionAnalyzer.cs @ 5759

Last change on this file since 5759 was 5759, checked in by mkommend, 14 years ago

#1418:

  • Worked on IntRange and DoubleRange
  • Updated evaluators, analyzers, problems and problem data to use IntRanges
  • Removed properties to access the value of LookupParameter
  • Corrected files.txt
File size: 4.5 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2011 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.Data;
25using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
26using HeuristicLab.Parameters;
27using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
28
29namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression {
30  /// <summary>
31  /// An operator that analyzes the validation best symbolic regression solution for multi objective symbolic regression problems.
32  /// </summary>
33  [Item("SymbolicRegressionMultiObjectiveValidationBestSolutionAnalyzer", "An operator that analyzes the validation best symbolic regression solution for multi objective symbolic regression problems.")]
34  [StorableClass]
35  public sealed class SymbolicRegressionMultiObjectiveValidationBestSolutionAnalyzer : SymbolicDataAnalysisMultiObjectiveValidationBestSolutionAnalyzer<ISymbolicRegressionSolution, ISymbolicRegressionMultiObjectiveEvaluator, IRegressionProblemData>,
36    ISymbolicDataAnalysisBoundedOperator {
37    private const string UpperEstimationLimitParameterName = "UpperEstimationLimit";
38    private const string LowerEstimationLimitParameterName = "LowerEstimationLimit";
39    private const string ApplyLinearScalingParameterName = "ApplyLinearScaling";
40
41    #region parameter properties
42    public IValueLookupParameter<DoubleValue> UpperEstimationLimitParameter {
43      get { return (IValueLookupParameter<DoubleValue>)Parameters[UpperEstimationLimitParameterName]; }
44    }
45
46    public IValueLookupParameter<DoubleValue> LowerEstimationLimitParameter {
47      get { return (IValueLookupParameter<DoubleValue>)Parameters[LowerEstimationLimitParameterName]; }
48    }
49    public IValueParameter<BoolValue> ApplyLinearScalingParameter {
50      get { return (IValueParameter<BoolValue>)Parameters[ApplyLinearScalingParameterName]; }
51    }
52    #endregion
53
54    #region properties
55    public BoolValue ApplyLinearScaling {
56      get { return ApplyLinearScalingParameter.Value; }
57    }
58    #endregion
59    [StorableConstructor]
60    private SymbolicRegressionMultiObjectiveValidationBestSolutionAnalyzer(bool deserializing) : base(deserializing) { }
61    private SymbolicRegressionMultiObjectiveValidationBestSolutionAnalyzer(SymbolicRegressionMultiObjectiveValidationBestSolutionAnalyzer original, Cloner cloner) : base(original, cloner) { }
62    public SymbolicRegressionMultiObjectiveValidationBestSolutionAnalyzer()
63      : base() {
64      Parameters.Add(new ValueLookupParameter<DoubleValue>(UpperEstimationLimitParameterName, "The upper limit for the estimated values produced by the symbolic regression model."));
65      Parameters.Add(new ValueLookupParameter<DoubleValue>(LowerEstimationLimitParameterName, "The lower limit for the estimated values produced by the symbolic regression model."));
66      Parameters.Add(new ValueParameter<BoolValue>(ApplyLinearScalingParameterName, "Flag that indicates if the produced symbolic regression solution should be linearly scaled.", new BoolValue(true)));
67    }
68    public override IDeepCloneable Clone(Cloner cloner) {
69      return new SymbolicRegressionMultiObjectiveValidationBestSolutionAnalyzer(this, cloner);
70    }
71
72    protected override ISymbolicRegressionSolution CreateSolution(ISymbolicExpressionTree bestTree, double[] bestQuality) {
73      var model = new SymbolicRegressionModel(bestTree, SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, LowerEstimationLimitParameter.ActualValue.Value, UpperEstimationLimitParameter.ActualValue.Value);
74      var solution = new SymbolicRegressionSolution(model, ProblemDataParameter.ActualValue);
75      if (ApplyLinearScaling.Value)
76        solution.ScaleModel();
77      return solution;
78    }
79  }
80}
Note: See TracBrowser for help on using the repository browser.