[5607] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[7259] | 3 | * Copyright (C) 2002-2012 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[5607] | 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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[7721] | 22 | using System;
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[5607] | 23 | using System.Collections.Generic;
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| 24 | using System.Linq;
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| 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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| 29 | using HeuristicLab.Optimization;
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| 30 | using HeuristicLab.Parameters;
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| 31 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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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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[5747] | 39 | public abstract class SymbolicDataAnalysisSingleObjectiveValidationBestSolutionAnalyzer<S, T, U> : SymbolicDataAnalysisSingleObjectiveValidationAnalyzer<T, U>
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[5607] | 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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[5722] | 70 | Parameters.Add(new LookupParameter<S>(ValidationBestSolutionParameterName, "The validation best symbolic data analyis solution."));
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[5607] | 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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[7721] | 75 | IEnumerable<int> rows = GenerateRowsToEvaluate();
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| 76 | if (!rows.Any()) return base.Apply();
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| 77 |
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[5607] | 78 | #region find best tree
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[7721] | 79 | var evaluator = EvaluatorParameter.ActualValue;
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| 80 | var problemData = ProblemDataParameter.ActualValue;
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| 81 | double bestValidationQuality = Maximization.Value ? double.NegativeInfinity : double.PositiveInfinity;
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[5607] | 82 | ISymbolicExpressionTree bestTree = null;
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[5882] | 83 | ISymbolicExpressionTree[] tree = SymbolicExpressionTree.ToArray();
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[5759] | 84 |
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[7721] | 85 | // sort is ascending and we take the first n% => order so that best solutions are smallest
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| 86 | // sort order is determined by maximization parameter
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| 87 | double[] trainingQuality;
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| 88 | if (Maximization.Value) {
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| 89 | // largest values must be sorted first
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| 90 | trainingQuality = Quality.Select(x => -x.Value).ToArray();
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| 91 | } else {
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| 92 | // smallest values must be sorted first
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| 93 | trainingQuality = Quality.Select(x => x.Value).ToArray();
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| 94 | }
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| 95 |
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| 96 | // sort trees by training qualities
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| 97 | Array.Sort(trainingQuality, tree);
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| 98 |
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| 99 | // number of best training solutions to validate (at least 1)
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| 100 | int topN = (int)Math.Max(tree.Length * PercentageOfBestSolutionsParameter.ActualValue.Value, 1);
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| 101 |
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[5722] | 102 | IExecutionContext childContext = (IExecutionContext)ExecutionContext.CreateChildOperation(evaluator);
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[7721] | 103 | // evaluate best n training trees on validiation set
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[6728] | 104 | var quality = tree
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[7721] | 105 | .Take(topN)
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[6728] | 106 | .AsParallel()
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| 107 | .Select(t => evaluator.Evaluate(childContext, t, problemData, rows))
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| 108 | .ToArray();
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| 109 |
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[7721] | 110 | for (int i = 0; i < quality.Length; i++) {
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| 111 | if (IsBetter(quality[i], bestValidationQuality, Maximization.Value)) {
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| 112 | bestValidationQuality = quality[i];
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[5607] | 113 | bestTree = tree[i];
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| 114 | }
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| 115 | }
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| 116 | #endregion
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| 117 |
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| 118 | var results = ResultCollection;
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| 119 | if (ValidationBestSolutionQuality == null ||
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[7721] | 120 | IsBetter(bestValidationQuality, ValidationBestSolutionQuality.Value, Maximization.Value)) {
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| 121 | ValidationBestSolution = CreateSolution(bestTree, bestValidationQuality);
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| 122 | ValidationBestSolutionQuality = new DoubleValue(bestValidationQuality);
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[5607] | 123 |
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[5747] | 124 | if (!results.ContainsKey(ValidationBestSolutionParameter.Name)) {
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| 125 | results.Add(new Result(ValidationBestSolutionParameter.Name, ValidationBestSolutionParameter.Description, ValidationBestSolution));
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| 126 | results.Add(new Result(ValidationBestSolutionQualityParameter.Name, ValidationBestSolutionQualityParameter.Description, ValidationBestSolutionQuality));
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[5607] | 127 | } else {
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[5747] | 128 | results[ValidationBestSolutionParameter.Name].Value = ValidationBestSolution;
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| 129 | results[ValidationBestSolutionQualityParameter.Name].Value = ValidationBestSolutionQuality;
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[5607] | 130 | }
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| 131 | }
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| 132 | return base.Apply();
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| 133 | }
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| 134 |
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| 135 | protected abstract S CreateSolution(ISymbolicExpressionTree bestTree, double bestQuality);
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| 136 |
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| 137 | private bool IsBetter(double lhs, double rhs, bool maximization) {
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| 138 | if (maximization) return lhs > rhs;
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| 139 | else return lhs < rhs;
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| 140 | }
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| 141 | }
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| 142 | }
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