[3442] | 1 | #region License Information
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| 2 | /* HeuristicLab
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| 3 | * Copyright (C) 2002-2010 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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| 4 | *
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| 5 | * This file is part of HeuristicLab.
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| 6 | *
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| 7 | * HeuristicLab is free software: you can redistribute it and/or modify
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| 8 | * it under the terms of the GNU General Public License as published by
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| 9 | * the Free Software Foundation, either version 3 of the License, or
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| 10 | * (at your option) any later version.
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| 11 | *
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| 12 | * HeuristicLab is distributed in the hope that it will be useful,
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| 13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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| 14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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| 15 | * GNU General Public License for more details.
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| 16 | *
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| 17 | * You should have received a copy of the GNU General Public License
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| 18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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| 19 | */
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| 20 | #endregion
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| 21 |
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| 22 | using System.Linq;
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| 23 | using HeuristicLab.Common;
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| 24 | using HeuristicLab.Core;
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| 25 | using HeuristicLab.Data;
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| 26 | using HeuristicLab.Operators;
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| 27 | using HeuristicLab.Optimization;
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| 28 | using HeuristicLab.Parameters;
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| 29 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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| 30 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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| 31 |
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| 32 | namespace HeuristicLab.Problems.DataAnalysis.Regression.Symbolic {
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| 33 | /// <summary>
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| 34 | /// An operator for visualizing the best symbolic regression solution based on the validation set.
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| 35 | /// </summary>
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| 36 | [Item("BestSymbolicExpressionTreeVisualizer", "An operator for visualizing the best symbolic regression solution based on the validation set.")]
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| 37 | [StorableClass]
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| 38 | public sealed class BestValidationSymbolicRegressionSolutionVisualizer : SingleSuccessorOperator, ISingleObjectiveSolutionsVisualizer, ISolutionsVisualizer {
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| 39 | private const string SymbolicRegressionModelParameterName = "SymbolicRegressionModel";
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| 40 | private const string DataAnalysisProblemDataParameterName = "DataAnalysisProblemData";
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| 41 | private const string BestValidationSolutionParameterName = "BestValidationSolution";
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| 42 | private const string QualityParameterName = "Quality";
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| 43 | public ILookupParameter<ItemArray<SymbolicExpressionTree>> SymbolicExpressionTreeParameter {
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| 44 | get { return (ILookupParameter<ItemArray<SymbolicExpressionTree>>)Parameters[SymbolicRegressionModelParameterName]; }
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| 45 | }
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| 46 | public ILookupParameter<DataAnalysisProblemData> DataAnalysisProblemDataParameter {
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| 47 | get { return (ILookupParameter<DataAnalysisProblemData>)Parameters[DataAnalysisProblemDataParameterName]; }
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| 48 | }
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| 49 | public ILookupParameter<SymbolicRegressionSolution> BestValidationSolutionParameter {
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| 50 | get { return (ILookupParameter<SymbolicRegressionSolution>)Parameters[BestValidationSolutionParameterName]; }
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| 51 | }
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| 52 | ILookupParameter ISolutionsVisualizer.VisualizationParameter {
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| 53 | get { return BestValidationSolutionParameter; }
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| 54 | }
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| 55 |
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| 56 | public ILookupParameter<ItemArray<DoubleValue>> QualityParameter {
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| 57 | get { return (ILookupParameter<ItemArray<DoubleValue>>)Parameters[QualityParameterName]; }
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| 58 | }
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| 59 |
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| 60 | public BestValidationSymbolicRegressionSolutionVisualizer()
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| 61 | : base() {
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| 62 | Parameters.Add(new SubScopesLookupParameter<SymbolicExpressionTree>(SymbolicRegressionModelParameterName, "The symbolic regression solutions from which the best solution should be visualized."));
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| 63 | Parameters.Add(new SubScopesLookupParameter<DoubleValue>(QualityParameterName, "The quality of the symbolic regression solutions."));
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| 64 | Parameters.Add(new LookupParameter<DataAnalysisProblemData>(DataAnalysisProblemDataParameterName, "The symbolic regression problme data on which the best solution should be evaluated."));
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| 65 | Parameters.Add(new LookupParameter<SymbolicRegressionSolution>(BestValidationSolutionParameterName, "The best symbolic expression tree based on the validation data for the symbolic regression problem."));
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| 66 | Parameters.Add(new LookupParameter<ResultCollection>("Results"));
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| 67 | }
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| 68 |
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| 69 | public override IOperation Apply() {
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| 70 | ItemArray<SymbolicExpressionTree> expressions = SymbolicExpressionTreeParameter.ActualValue;
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| 71 | DataAnalysisProblemData problemData = DataAnalysisProblemDataParameter.ActualValue;
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| 72 | ItemArray<DoubleValue> qualities = QualityParameter.ActualValue;
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| 73 |
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| 74 | var bestExpressionIndex = (from index in Enumerable.Range(0, qualities.Count())
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| 75 | select new { Index = index, Quality = qualities[index] }).OrderBy(x => x.Quality).Select(x => x.Index).First();
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| 76 |
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| 77 | var bestExpression = expressions[bestExpressionIndex];
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| 78 | SymbolicRegressionSolution bestSolution = BestValidationSolutionParameter.ActualValue;
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| 79 | if (bestSolution == null) BestValidationSolutionParameter.ActualValue = CreateDataAnalysisSolution(problemData, bestExpression);
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| 80 | else {
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| 81 | bestSolution.Model = CreateModel(problemData, bestExpression);
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| 82 | }
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| 83 | // ((ResultCollection)Parameters["Results"].ActualValue).Add(new Result("ValidationMSE", new DoubleValue(3.15)));
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| 84 | return base.Apply();
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| 85 | }
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| 86 |
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| 87 | private SymbolicRegressionModel CreateModel(DataAnalysisProblemData problemData, SymbolicExpressionTree expression) {
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| 88 | return new SymbolicRegressionModel(expression, problemData.InputVariables.Select(x => x.Value));
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| 89 | }
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| 90 |
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| 91 | private SymbolicRegressionSolution CreateDataAnalysisSolution(DataAnalysisProblemData problemData, SymbolicExpressionTree expression) {
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| 92 | return new SymbolicRegressionSolution(problemData, CreateModel(problemData, expression));
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| 93 | }
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| 94 | }
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| 95 | }
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