[5505] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[17180] | 3 | * Copyright (C) Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[5505] | 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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[12147] | 22 | using System;
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[5505] | 23 | using System.Collections.Generic;
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[16978] | 24 | using HEAL.Attic;
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[5505] | 25 | using HeuristicLab.Common;
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| 26 | using HeuristicLab.Core;
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| 27 | using HeuristicLab.Data;
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| 28 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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[16499] | 29 | using HeuristicLab.Parameters;
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[5505] | 30 |
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[5618] | 31 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression {
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[16499] | 32 | [Item("Pearson R² & Average Similarity Evaluator", "Calculates the Pearson R² and the average similarity of a symbolic regression solution candidate.")]
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[16565] | 33 | [StorableType("FE514989-E619-48B8-AC8E-9A2202708F65")]
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[16499] | 34 | public class PearsonRSquaredAverageSimilarityEvaluator : SymbolicRegressionMultiObjectiveEvaluator {
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| 35 | private const string StrictSimilarityParameterName = "StrictSimilarity";
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[16978] | 36 | private const string AverageSimilarityParameterName = "AverageSimilarity";
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[16499] | 37 |
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| 38 | private readonly object locker = new object();
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| 39 |
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[16978] | 40 | private readonly SymbolicDataAnalysisExpressionTreeAverageSimilarityCalculator SimilarityCalculator = new SymbolicDataAnalysisExpressionTreeAverageSimilarityCalculator();
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| 41 |
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[16499] | 42 | public IFixedValueParameter<BoolValue> StrictSimilarityParameter {
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| 43 | get { return (IFixedValueParameter<BoolValue>)Parameters[StrictSimilarityParameterName]; }
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| 44 | }
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| 45 |
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[16978] | 46 | public ILookupParameter<DoubleValue> AverageSimilarityParameter {
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| 47 | get { return (ILookupParameter<DoubleValue>)Parameters[AverageSimilarityParameterName]; }
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| 48 | }
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| 49 |
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[16499] | 50 | public bool StrictSimilarity {
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| 51 | get { return StrictSimilarityParameter.Value.Value; }
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| 52 | }
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| 53 |
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[5505] | 54 | [StorableConstructor]
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[16565] | 55 | protected PearsonRSquaredAverageSimilarityEvaluator(StorableConstructorFlag _) : base(_) { }
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[16499] | 56 | protected PearsonRSquaredAverageSimilarityEvaluator(PearsonRSquaredAverageSimilarityEvaluator original, Cloner cloner)
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[5505] | 57 | : base(original, cloner) {
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| 58 | }
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| 59 | public override IDeepCloneable Clone(Cloner cloner) {
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[16499] | 60 | return new PearsonRSquaredAverageSimilarityEvaluator(this, cloner);
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[5505] | 61 | }
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| 62 |
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[16499] | 63 | public PearsonRSquaredAverageSimilarityEvaluator() : base() {
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| 64 | Parameters.Add(new FixedValueParameter<BoolValue>(StrictSimilarityParameterName, "Use strict similarity calculation.", new BoolValue(false)));
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[16978] | 65 | Parameters.Add(new LookupParameter<DoubleValue>(AverageSimilarityParameterName));
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[16499] | 66 | }
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[11310] | 67 |
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[16978] | 68 | public override IEnumerable<bool> Maximization { get { return new bool[2] { true, false }; } } // maximize R² and minimize average similarity
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[5514] | 69 |
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[10291] | 70 | public override IOperation InstrumentedApply() {
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[5505] | 71 | IEnumerable<int> rows = GenerateRowsToEvaluate();
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[5851] | 72 | var solution = SymbolicExpressionTreeParameter.ActualValue;
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[11310] | 73 | var problemData = ProblemDataParameter.ActualValue;
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| 74 | var interpreter = SymbolicDataAnalysisTreeInterpreterParameter.ActualValue;
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| 75 | var estimationLimits = EstimationLimitsParameter.ActualValue;
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| 76 | var applyLinearScaling = ApplyLinearScalingParameter.ActualValue.Value;
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| 77 |
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| 78 | if (UseConstantOptimization) {
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[13670] | 79 | SymbolicRegressionConstantOptimizationEvaluator.OptimizeConstants(interpreter, solution, problemData, rows, applyLinearScaling, ConstantOptimizationIterations, updateVariableWeights: ConstantOptimizationUpdateVariableWeights, lowerEstimationLimit: estimationLimits.Lower, upperEstimationLimit: estimationLimits.Upper);
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[11310] | 80 | }
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[5505] | 81 |
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[16978] | 82 | double r2 = SymbolicRegressionSingleObjectivePearsonRSquaredEvaluator.Calculate(interpreter, solution, estimationLimits.Lower, estimationLimits.Upper, problemData, rows, applyLinearScaling);
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[16499] | 83 |
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[16978] | 84 | if (DecimalPlaces >= 0)
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| 85 | r2 = Math.Round(r2, DecimalPlaces);
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[16499] | 86 |
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[16978] | 87 | lock (locker) {
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| 88 | if (AverageSimilarityParameter.ActualValue == null) {
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| 89 | var context = new ExecutionContext(null, SimilarityCalculator, ExecutionContext.Scope.Parent);
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| 90 | SimilarityCalculator.StrictSimilarity = StrictSimilarity;
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| 91 | SimilarityCalculator.Execute(context, CancellationToken);
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[16499] | 92 | }
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| 93 | }
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[16978] | 94 | var avgSimilarity = AverageSimilarityParameter.ActualValue.Value;
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[16499] | 95 |
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[16978] | 96 | QualitiesParameter.ActualValue = new DoubleArray(new[] { r2, avgSimilarity });
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| 97 | return base.InstrumentedApply();
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[5505] | 98 | }
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[5613] | 99 |
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| 100 | public override double[] Evaluate(IExecutionContext context, ISymbolicExpressionTree tree, IRegressionProblemData problemData, IEnumerable<int> rows) {
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[5722] | 101 | SymbolicDataAnalysisTreeInterpreterParameter.ExecutionContext = context;
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[16978] | 102 | AverageSimilarityParameter.ExecutionContext = context;
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[5770] | 103 | EstimationLimitsParameter.ExecutionContext = context;
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[8664] | 104 | ApplyLinearScalingParameter.ExecutionContext = context;
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[5722] | 105 |
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[16978] | 106 | var estimationLimits = EstimationLimitsParameter.ActualValue;
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| 107 | var applyLinearScaling = ApplyLinearScalingParameter.ActualValue.Value;
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[5722] | 108 |
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[16978] | 109 | double r2 = SymbolicRegressionSingleObjectivePearsonRSquaredEvaluator.Calculate(SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, tree, estimationLimits.Lower, estimationLimits.Upper, problemData, rows, applyLinearScaling);
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| 110 |
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| 111 | lock (locker) {
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| 112 | if (AverageSimilarityParameter.ActualValue == null) {
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| 113 | var ctx = new ExecutionContext(null, SimilarityCalculator, context.Scope.Parent);
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| 114 | SimilarityCalculator.StrictSimilarity = StrictSimilarity;
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| 115 | SimilarityCalculator.Execute(context, CancellationToken);
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| 116 | }
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| 117 | }
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| 118 | var avgSimilarity = AverageSimilarityParameter.ActualValue.Value;
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| 119 |
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[5722] | 120 | SymbolicDataAnalysisTreeInterpreterParameter.ExecutionContext = null;
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[5770] | 121 | EstimationLimitsParameter.ExecutionContext = null;
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[8664] | 122 | ApplyLinearScalingParameter.ExecutionContext = null;
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[5722] | 123 |
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[16978] | 124 | return new[] { r2, avgSimilarity };
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[5613] | 125 | }
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[5505] | 126 | }
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| 127 | }
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