1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2015 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.Analysis;
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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.Parameters;
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29 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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30 |
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31 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Classification {
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32 | [Item("SymbolicClassificationPhenotypicDiversityAnalyzer", "An analyzer which calculates diversity based on the phenotypic distance between trees")]
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33 | [StorableClass]
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34 | public class SymbolicClassificationPhenotypicDiversityAnalyzer : SingleObjectivePopulationDiversityAnalyzer {
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35 | #region parameter names
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36 | private const string SymbolicExpressionTreeParameterName = "SymbolicExpressionTree";
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37 | private const string EvaluatedValuesParameterName = "EstimatedValues";
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38 | private const string SymbolicDataAnalysisTreeInterpreterParameterName = "SymbolicExpressionTreeInterpreter";
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39 | private const string ProblemDataParameterName = "ProblemData";
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40 | private const string ModelCreatorParameterName = "ModelCreator";
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41 | private const string EstimationLimitsParameterName = "EstimationLimits";
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42 | private const string UseClassValuesParameterName = "UseClassValues";
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43 | #endregion
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44 |
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45 | #region parameter properties
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46 | public IScopeTreeLookupParameter<ISymbolicExpressionTree> SymbolicExpressionTreeParameter {
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47 | get { return (IScopeTreeLookupParameter<ISymbolicExpressionTree>)Parameters[SymbolicExpressionTreeParameterName]; }
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48 | }
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49 | private IScopeTreeLookupParameter<DoubleArray> EvaluatedValuesParameter {
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50 | get { return (IScopeTreeLookupParameter<DoubleArray>)Parameters[EvaluatedValuesParameterName]; }
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51 | }
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52 | public ILookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter> SymbolicDataAnalysisTreeInterpreterParameter {
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53 | get { return (ILookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter>)Parameters[SymbolicDataAnalysisTreeInterpreterParameterName]; }
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54 | }
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55 | public ILookupParameter<ISymbolicDiscriminantFunctionClassificationModelCreator> ModelCreatorParameter {
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56 | get { return (ILookupParameter<ISymbolicDiscriminantFunctionClassificationModelCreator>)Parameters[ModelCreatorParameterName]; }
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57 | }
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58 | public IValueLookupParameter<IClassificationProblemData> ProblemDataParameter {
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59 | get { return (IValueLookupParameter<IClassificationProblemData>)Parameters[ProblemDataParameterName]; }
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60 | }
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61 | public IValueLookupParameter<DoubleLimit> EstimationLimitsParameter {
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62 | get { return (IValueLookupParameter<DoubleLimit>)Parameters[EstimationLimitsParameterName]; }
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63 | }
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64 | public IFixedValueParameter<BoolValue> UseClassValuesParameter {
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65 | get { return (IFixedValueParameter<BoolValue>)Parameters[UseClassValuesParameterName]; }
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66 | }
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67 | #endregion
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68 |
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69 | #region properties
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70 | private bool UseClassValues {
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71 | get { return UseClassValuesParameter.Value.Value; }
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72 | set { UseClassValuesParameter.Value.Value = value; }
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73 | }
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74 | #endregion
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75 |
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76 | public SymbolicClassificationPhenotypicDiversityAnalyzer() {
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77 | SimilarityCalculator = new SymbolicExpressionTreePhenotypicSimilarityCalculator { SolutionVariableName = "SymbolicExpressionTree", QualityVariableName = "Quality" };
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78 | #region add parameters
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79 | Parameters.Add(new ScopeTreeLookupParameter<ISymbolicExpressionTree>(SymbolicExpressionTreeParameterName, "The symbolic expression trees."));
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80 | Parameters.Add(new ScopeTreeLookupParameter<DoubleArray>(EvaluatedValuesParameterName, "Intermediate estimated values to be saved in the scopes."));
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81 | Parameters.Add(new LookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter>(SymbolicDataAnalysisTreeInterpreterParameterName, "The interpreter that should be used to calculate the output values of the symbolic data analysis tree."));
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82 | Parameters.Add(new ValueLookupParameter<IClassificationProblemData>(ProblemDataParameterName, "The problem data on which the symbolic data analysis solution should be evaluated."));
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83 | Parameters.Add(new LookupParameter<ISymbolicDiscriminantFunctionClassificationModelCreator>(ModelCreatorParameterName, "The model creator for creating discriminant function classification models."));
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84 | Parameters.Add(new ValueLookupParameter<DoubleLimit>(EstimationLimitsParameterName, "The upper and lower limit that should be used as cut off value for the output values of symbolic data analysis trees."));
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85 | Parameters.Add(new FixedValueParameter<BoolValue>(UseClassValuesParameterName, "Specifies whether the raw estimated values of the tree or the corresponding class values should be used for similarity calculation.", new BoolValue(false)));
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86 | #endregion
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87 | }
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88 |
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89 | [StorableConstructor]
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90 | protected SymbolicClassificationPhenotypicDiversityAnalyzer(bool deserializing)
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91 | : base(deserializing) {
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92 | }
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93 |
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94 | public override IDeepCloneable Clone(Cloner cloner) {
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95 | return new SymbolicClassificationPhenotypicDiversityAnalyzer(this, cloner);
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96 | }
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97 |
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98 | private SymbolicClassificationPhenotypicDiversityAnalyzer(SymbolicClassificationPhenotypicDiversityAnalyzer original, Cloner cloner)
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99 | : base(original, cloner) {
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100 | }
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101 |
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102 | public override IOperation Apply() {
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103 | var trees = SymbolicExpressionTreeParameter.ActualValue;
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104 | var interpreter = SymbolicDataAnalysisTreeInterpreterParameter.ActualValue;
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105 | var problemData = ProblemDataParameter.ActualValue;
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106 | var ds = ProblemDataParameter.ActualValue.Dataset;
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107 | var rows = ProblemDataParameter.ActualValue.TrainingIndices;
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108 | var modelCreator = ModelCreatorParameter.ActualValue;
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109 | var estimationLimits = EstimationLimitsParameter.ActualValue;
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110 | var evaluatedValues = new ItemArray<DoubleArray>(trees.Length);
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111 | for (int i = 0; i < trees.Length; ++i) {
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112 | var model = (IDiscriminantFunctionClassificationModel)modelCreator.CreateSymbolicDiscriminantFunctionClassificationModel(trees[i], interpreter, estimationLimits.Lower, estimationLimits.Upper);
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113 | model.RecalculateModelParameters(problemData, rows);
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114 | var values = UseClassValues ? model.GetEstimatedClassValues(ds, rows) : model.GetEstimatedValues(ds, rows);
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115 | evaluatedValues[i] = new DoubleArray(values.ToArray());
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116 | }
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117 | EvaluatedValuesParameter.ActualValue = evaluatedValues;
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118 | return base.Apply();
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119 | }
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120 | }
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121 | }
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