1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2011 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.Collections.Generic;
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23 | using System.Linq;
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24 | using HeuristicLab.Common;
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25 | using HeuristicLab.Core;
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26 | using HeuristicLab.Data;
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27 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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28 | using HeuristicLab.Optimization;
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29 | using HeuristicLab.Parameters;
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30 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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31 | using HeuristicLab.Random;
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32 |
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33 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
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34 | /// <summary>
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35 | /// An operator that analyzes the validation best symbolic data analysis solution for single objective symbolic data analysis problems.
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36 | /// </summary>
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37 | [Item("SymbolicDataAnalysisSingleObjectiveValidationBestSolutionAnalyzer", "An operator that analyzes the validation best symbolic data analysis solution for single objective symbolic data analysis problems.")]
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38 | [StorableClass]
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39 | public abstract class SymbolicDataAnalysisSingleObjectiveValidationBestSolutionAnalyzer<S, T, U> : SymbolicDataAnalysisSingleObjectiveValidationAnalyzer<T, U>
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40 | where S : class, ISymbolicDataAnalysisSolution
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41 | where T : class, ISymbolicDataAnalysisSingleObjectiveEvaluator<U>
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42 | where U : class, IDataAnalysisProblemData {
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43 | private const string ValidationBestSolutionParameterName = "Best validation solution";
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44 | private const string ValidationBestSolutionQualityParameterName = "Best validation solution quality";
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45 |
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46 | #region parameter properties
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47 | public ILookupParameter<S> ValidationBestSolutionParameter {
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48 | get { return (ILookupParameter<S>)Parameters[ValidationBestSolutionParameterName]; }
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49 | }
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50 | public ILookupParameter<DoubleValue> ValidationBestSolutionQualityParameter {
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51 | get { return (ILookupParameter<DoubleValue>)Parameters[ValidationBestSolutionQualityParameterName]; }
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52 | }
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53 | #endregion
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54 | #region properties
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55 | public S ValidationBestSolution {
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56 | get { return ValidationBestSolutionParameter.ActualValue; }
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57 | set { ValidationBestSolutionParameter.ActualValue = value; }
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58 | }
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59 | public DoubleValue ValidationBestSolutionQuality {
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60 | get { return ValidationBestSolutionQualityParameter.ActualValue; }
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61 | set { ValidationBestSolutionQualityParameter.ActualValue = value; }
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62 | }
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63 | #endregion
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64 |
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65 | [StorableConstructor]
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66 | protected SymbolicDataAnalysisSingleObjectiveValidationBestSolutionAnalyzer(bool deserializing) : base(deserializing) { }
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67 | protected SymbolicDataAnalysisSingleObjectiveValidationBestSolutionAnalyzer(SymbolicDataAnalysisSingleObjectiveValidationBestSolutionAnalyzer<S, T, U> original, Cloner cloner) : base(original, cloner) { }
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68 | public SymbolicDataAnalysisSingleObjectiveValidationBestSolutionAnalyzer()
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69 | : base() {
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70 | Parameters.Add(new LookupParameter<S>(ValidationBestSolutionParameterName, "The validation best symbolic data analyis solution."));
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71 | Parameters.Add(new LookupParameter<DoubleValue>(ValidationBestSolutionQualityParameterName, "The quality of the validation best symbolic data analysis solution."));
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72 | }
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73 |
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74 | public override IOperation Apply() {
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75 | #region find best tree
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76 | double bestQuality = Maximization.Value ? double.NegativeInfinity : double.PositiveInfinity;
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77 | ISymbolicExpressionTree bestTree = null;
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78 | ISymbolicExpressionTree[] tree = SymbolicExpressionTrees.ToArray();
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79 | double[] quality = new double[tree.Length];
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80 | var evaluator = EvaluatorParameter.ActualValue;
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81 | int start = ValidationPartitionParameter.ActualValue.Start;
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82 | int end = ValidationPartitionParameter.ActualValue.End;
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83 | int count = (int)((end - start) * RelativeNumberOfEvaluatedSamplesParameter.ActualValue.Value);
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84 | if (count <= 0) return base.Apply();
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85 |
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86 | IEnumerable<int> rows = RandomEnumerable.SampleRandomNumbers(start, end, count);
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87 | IExecutionContext childContext = (IExecutionContext)ExecutionContext.CreateChildOperation(evaluator);
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88 | for (int i = 0; i < tree.Length; i++) {
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89 | quality[i] = evaluator.Evaluate(childContext, tree[i], ProblemDataParameter.ActualValue, rows);
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90 | if (IsBetter(quality[i], bestQuality, Maximization.Value)) {
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91 | bestQuality = quality[i];
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92 | bestTree = tree[i];
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93 | }
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94 | }
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95 | #endregion
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96 |
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97 | var results = ResultCollection;
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98 | if (ValidationBestSolutionQuality == null ||
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99 | IsBetter(bestQuality, ValidationBestSolutionQuality.Value, Maximization.Value)) {
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100 | ValidationBestSolution = CreateSolution(bestTree, bestQuality);
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101 | ValidationBestSolutionQuality = new DoubleValue(bestQuality);
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102 |
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103 | if (!results.ContainsKey(ValidationBestSolutionParameter.Name)) {
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104 | results.Add(new Result(ValidationBestSolutionParameter.Name, ValidationBestSolutionParameter.Description, ValidationBestSolution));
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105 | results.Add(new Result(ValidationBestSolutionQualityParameter.Name, ValidationBestSolutionQualityParameter.Description, ValidationBestSolutionQuality));
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106 | } else {
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107 | results[ValidationBestSolutionParameter.Name].Value = ValidationBestSolution;
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108 | results[ValidationBestSolutionQualityParameter.Name].Value = ValidationBestSolutionQuality;
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109 | }
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110 | }
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111 | return base.Apply();
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112 | }
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113 |
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114 | protected abstract S CreateSolution(ISymbolicExpressionTree bestTree, double bestQuality);
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115 |
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116 | private bool IsBetter(double lhs, double rhs, bool maximization) {
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117 | if (maximization) return lhs > rhs;
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118 | else return lhs < rhs;
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119 | }
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120 | }
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121 | }
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