[5618] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[12012] | 3 | * Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[5618] | 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 | using System.Linq;
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| 22 | using HeuristicLab.Common;
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| 23 | using HeuristicLab.Core;
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[12103] | 24 | using HeuristicLab.Optimization;
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[5716] | 25 | using HeuristicLab.Parameters;
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[5618] | 26 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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| 27 |
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| 28 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Classification {
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| 29 | [Item("Symbolic Classification Problem (single objective)", "Represents a single objective symbolic classfication problem.")]
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| 30 | [StorableClass]
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| 31 | [Creatable("Problems")]
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[5733] | 32 | public class SymbolicClassificationSingleObjectiveProblem : SymbolicDataAnalysisSingleObjectiveProblem<IClassificationProblemData, ISymbolicClassificationSingleObjectiveEvaluator, ISymbolicDataAnalysisSolutionCreator>, IClassificationProblem {
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[5618] | 33 | private const double PunishmentFactor = 10;
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[5685] | 34 | private const int InitialMaximumTreeDepth = 8;
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| 35 | private const int InitialMaximumTreeLength = 25;
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[5770] | 36 | private const string EstimationLimitsParameterName = "EstimationLimits";
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| 37 | private const string EstimationLimitsParameterDescription = "The lower and upper limit for the estimated value that can be returned by the symbolic classification model.";
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[8594] | 38 | private const string ModelCreatorParameterName = "ModelCreator";
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[5618] | 39 |
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[5685] | 40 | #region parameter properties
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[5770] | 41 | public IFixedValueParameter<DoubleLimit> EstimationLimitsParameter {
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| 42 | get { return (IFixedValueParameter<DoubleLimit>)Parameters[EstimationLimitsParameterName]; }
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[5685] | 43 | }
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[8594] | 44 | public IValueParameter<ISymbolicClassificationModelCreator> ModelCreatorParameter {
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| 45 | get { return (IValueParameter<ISymbolicClassificationModelCreator>)Parameters[ModelCreatorParameterName]; }
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| 46 | }
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[5685] | 47 | #endregion
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| 48 | #region properties
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[5770] | 49 | public DoubleLimit EstimationLimits {
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| 50 | get { return EstimationLimitsParameter.Value; }
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[5685] | 51 | }
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[8594] | 52 | public ISymbolicClassificationModelCreator ModelCreator {
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| 53 | get { return ModelCreatorParameter.Value; }
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| 54 | }
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[5685] | 55 | #endregion
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[5618] | 56 | [StorableConstructor]
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| 57 | protected SymbolicClassificationSingleObjectiveProblem(bool deserializing) : base(deserializing) { }
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[8175] | 58 | protected SymbolicClassificationSingleObjectiveProblem(SymbolicClassificationSingleObjectiveProblem original, Cloner cloner)
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| 59 | : base(original, cloner) {
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| 60 | RegisterEventHandlers();
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| 61 | }
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[5618] | 62 | public override IDeepCloneable Clone(Cloner cloner) { return new SymbolicClassificationSingleObjectiveProblem(this, cloner); }
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| 63 |
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| 64 | public SymbolicClassificationSingleObjectiveProblem()
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| 65 | : base(new ClassificationProblemData(), new SymbolicClassificationSingleObjectiveMeanSquaredErrorEvaluator(), new SymbolicDataAnalysisExpressionTreeCreator()) {
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[5847] | 66 | Parameters.Add(new FixedValueParameter<DoubleLimit>(EstimationLimitsParameterName, EstimationLimitsParameterDescription));
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[8594] | 67 | Parameters.Add(new ValueParameter<ISymbolicClassificationModelCreator>(ModelCreatorParameterName, "", new AccuracyMaximizingThresholdsModelCreator()));
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[5685] | 68 |
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[8664] | 69 | ApplyLinearScalingParameter.Value.Value = false;
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[5854] | 70 | EstimationLimitsParameter.Hidden = true;
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| 71 |
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[5685] | 72 | MaximumSymbolicExpressionTreeDepth.Value = InitialMaximumTreeDepth;
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| 73 | MaximumSymbolicExpressionTreeLength.Value = InitialMaximumTreeLength;
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| 74 |
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[8175] | 75 | RegisterEventHandlers();
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[6803] | 76 | ConfigureGrammarSymbols();
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[5685] | 77 | InitializeOperators();
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[5716] | 78 | UpdateEstimationLimits();
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[5618] | 79 | }
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| 80 |
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[8130] | 81 | [StorableHook(HookType.AfterDeserialization)]
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| 82 | private void AfterDeserialization() {
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[8883] | 83 | // BackwardsCompatibility3.4
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| 84 | #region Backwards compatible code, remove with 3.5
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[8594] | 85 | if (!Parameters.ContainsKey(ModelCreatorParameterName))
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| 86 | Parameters.Add(new ValueParameter<ISymbolicClassificationModelCreator>(ModelCreatorParameterName, "", new AccuracyMaximizingThresholdsModelCreator()));
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| 87 |
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[8130] | 88 | bool changed = false;
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| 89 | if (!Operators.OfType<SymbolicClassificationSingleObjectiveTrainingParetoBestSolutionAnalyzer>().Any()) {
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| 90 | Operators.Add(new SymbolicClassificationSingleObjectiveTrainingParetoBestSolutionAnalyzer());
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| 91 | changed = true;
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| 92 | }
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| 93 | if (!Operators.OfType<SymbolicClassificationSingleObjectiveValidationParetoBestSolutionAnalyzer>().Any()) {
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| 94 | Operators.Add(new SymbolicClassificationSingleObjectiveValidationParetoBestSolutionAnalyzer());
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| 95 | changed = true;
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| 96 | }
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| 97 | if (changed) ParameterizeOperators();
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[8883] | 98 | #endregion
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[8594] | 99 | RegisterEventHandlers();
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[8130] | 100 | }
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| 101 |
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[8175] | 102 | private void RegisterEventHandlers() {
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| 103 | SymbolicExpressionTreeGrammarParameter.ValueChanged += (o, e) => ConfigureGrammarSymbols();
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[8594] | 104 | ModelCreatorParameter.NameChanged += (o, e) => ParameterizeOperators();
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[8175] | 105 | }
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| 106 |
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[6803] | 107 | private void ConfigureGrammarSymbols() {
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| 108 | var grammar = SymbolicExpressionTreeGrammar as TypeCoherentExpressionGrammar;
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| 109 | if (grammar != null) grammar.ConfigureAsDefaultClassificationGrammar();
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| 110 | }
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| 111 |
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[5685] | 112 | private void InitializeOperators() {
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| 113 | Operators.Add(new SymbolicClassificationSingleObjectiveTrainingBestSolutionAnalyzer());
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| 114 | Operators.Add(new SymbolicClassificationSingleObjectiveValidationBestSolutionAnalyzer());
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[5747] | 115 | Operators.Add(new SymbolicClassificationSingleObjectiveOverfittingAnalyzer());
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[7734] | 116 | Operators.Add(new SymbolicClassificationSingleObjectiveTrainingParetoBestSolutionAnalyzer());
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| 117 | Operators.Add(new SymbolicClassificationSingleObjectiveValidationParetoBestSolutionAnalyzer());
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[12103] | 118 | Operators.Add(new SymbolicExpressionTreePhenotypicSimilarityCalculator());
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| 119 | Operators.Add(new SymbolicClassificationPhenotypicDiversityAnalyzer(Operators.OfType<SymbolicExpressionTreePhenotypicSimilarityCalculator>()));
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[5685] | 120 | ParameterizeOperators();
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| 121 | }
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| 122 |
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| 123 | private void UpdateEstimationLimits() {
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[8139] | 124 | if (ProblemData.TrainingIndices.Any()) {
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| 125 | var targetValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndices).ToList();
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[5618] | 126 | var mean = targetValues.Average();
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| 127 | var range = targetValues.Max() - targetValues.Min();
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[5770] | 128 | EstimationLimits.Upper = mean + PunishmentFactor * range;
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| 129 | EstimationLimits.Lower = mean - PunishmentFactor * range;
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[6754] | 130 | } else {
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| 131 | EstimationLimits.Upper = double.MaxValue;
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| 132 | EstimationLimits.Lower = double.MinValue;
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[5618] | 133 | }
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| 134 | }
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[5623] | 135 |
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[5685] | 136 | protected override void OnProblemDataChanged() {
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| 137 | base.OnProblemDataChanged();
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| 138 | UpdateEstimationLimits();
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| 139 | }
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| 140 |
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| 141 | protected override void ParameterizeOperators() {
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| 142 | base.ParameterizeOperators();
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[5770] | 143 | if (Parameters.ContainsKey(EstimationLimitsParameterName)) {
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| 144 | var operators = Parameters.OfType<IValueParameter>().Select(p => p.Value).OfType<IOperator>().Union(Operators);
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[8594] | 145 | foreach (var op in operators.OfType<ISymbolicDataAnalysisBoundedOperator>())
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[5770] | 146 | op.EstimationLimitsParameter.ActualName = EstimationLimitsParameter.Name;
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[8594] | 147 | foreach (var op in operators.OfType<ISymbolicClassificationModelCreatorOperator>())
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| 148 | op.ModelCreatorParameter.ActualName = ModelCreatorParameter.Name;
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[5685] | 149 | }
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[12103] | 150 |
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| 151 | foreach (var op in Operators.OfType<ISolutionSimilarityCalculator>()) {
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| 152 | op.SolutionVariableName = SolutionCreator.SymbolicExpressionTreeParameter.ActualName;
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| 153 | op.QualityVariableName = Evaluator.QualityParameter.ActualName;
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| 154 |
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| 155 | if (op is SymbolicExpressionTreePhenotypicSimilarityCalculator) {
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| 156 | var phenotypicSimilarityCalculator = (SymbolicExpressionTreePhenotypicSimilarityCalculator)op;
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| 157 | phenotypicSimilarityCalculator.ProblemData = ProblemData;
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| 158 | phenotypicSimilarityCalculator.Interpreter = SymbolicExpressionTreeInterpreter;
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| 159 | }
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| 160 | }
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[5685] | 161 | }
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[5618] | 162 | }
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| 163 | }
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