[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 |
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| 22 | using System.Linq;
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| 23 | using HeuristicLab.Common;
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| 24 | using HeuristicLab.Core;
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| 25 | using HeuristicLab.Data;
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[5716] | 26 | using HeuristicLab.Parameters;
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[5618] | 27 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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| 28 |
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| 29 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression {
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| 30 | [Item("Symbolic Regression Problem (multi objective)", "Represents a multi objective symbolic regression problem.")]
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| 31 | [StorableClass]
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| 32 | [Creatable("Problems")]
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[5733] | 33 | public class SymbolicRegressionMultiObjectiveProblem : SymbolicDataAnalysisMultiObjectiveProblem<IRegressionProblemData, ISymbolicRegressionMultiObjectiveEvaluator, ISymbolicDataAnalysisSolutionCreator>, IRegressionProblem {
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[5618] | 34 | private const double PunishmentFactor = 10;
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[5685] | 35 | private const int InitialMaximumTreeDepth = 8;
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| 36 | private const int InitialMaximumTreeLength = 25;
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[5770] | 37 | private const string EstimationLimitsParameterName = "EstimationLimits";
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| 38 | private const string EstimationLimitsParameterDescription = "The lower and upper limit for the estimated value that can be returned by the symbolic regression model.";
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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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| 44 | #endregion
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[5770] | 45 |
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[5685] | 46 | #region properties
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[5770] | 47 | public DoubleLimit EstimationLimits {
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| 48 | get { return EstimationLimitsParameter.Value; }
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[5685] | 49 | }
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[5770] | 50 |
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[5685] | 51 | #endregion
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[5770] | 52 |
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[5618] | 53 | [StorableConstructor]
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| 54 | protected SymbolicRegressionMultiObjectiveProblem(bool deserializing) : base(deserializing) { }
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[8175] | 55 | protected SymbolicRegressionMultiObjectiveProblem(SymbolicRegressionMultiObjectiveProblem original, Cloner cloner)
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| 56 | : base(original, cloner) {
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| 57 | RegisterEventHandlers();
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| 58 | }
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[5618] | 59 | public override IDeepCloneable Clone(Cloner cloner) { return new SymbolicRegressionMultiObjectiveProblem(this, cloner); }
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| 60 |
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| 61 | public SymbolicRegressionMultiObjectiveProblem()
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| 62 | : base(new RegressionProblemData(), new SymbolicRegressionMultiObjectivePearsonRSquaredTreeSizeEvaluator(), new SymbolicDataAnalysisExpressionTreeCreator()) {
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[5847] | 63 | Parameters.Add(new FixedValueParameter<DoubleLimit>(EstimationLimitsParameterName, EstimationLimitsParameterDescription));
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[5685] | 64 |
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[5854] | 65 | EstimationLimitsParameter.Hidden = true;
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| 66 |
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[8664] | 67 | ApplyLinearScalingParameter.Value.Value = true;
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[5742] | 68 | Maximization = new BoolArray(new bool[] { true, false });
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[5685] | 69 | MaximumSymbolicExpressionTreeDepth.Value = InitialMaximumTreeDepth;
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| 70 | MaximumSymbolicExpressionTreeLength.Value = InitialMaximumTreeLength;
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| 71 |
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[8175] | 72 | RegisterEventHandlers();
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[6803] | 73 | ConfigureGrammarSymbols();
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[5685] | 74 | InitializeOperators();
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[5716] | 75 | UpdateEstimationLimits();
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[5618] | 76 | }
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| 77 |
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[8175] | 78 | [StorableHook(HookType.AfterDeserialization)]
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| 79 | private void AfterDeserialization() {
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| 80 | RegisterEventHandlers();
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| 81 | }
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| 82 |
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| 83 | private void RegisterEventHandlers() {
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| 84 | SymbolicExpressionTreeGrammarParameter.ValueChanged += (o, e) => ConfigureGrammarSymbols();
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| 85 | }
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| 86 |
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[6803] | 87 | private void ConfigureGrammarSymbols() {
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| 88 | var grammar = SymbolicExpressionTreeGrammar as TypeCoherentExpressionGrammar;
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| 89 | if (grammar != null) grammar.ConfigureAsDefaultRegressionGrammar();
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| 90 | }
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| 91 |
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[5685] | 92 | private void InitializeOperators() {
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| 93 | Operators.Add(new SymbolicRegressionMultiObjectiveTrainingBestSolutionAnalyzer());
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| 94 | Operators.Add(new SymbolicRegressionMultiObjectiveValidationBestSolutionAnalyzer());
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| 95 | ParameterizeOperators();
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| 96 | }
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| 97 |
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| 98 | private void UpdateEstimationLimits() {
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[8139] | 99 | if (ProblemData.TrainingIndices.Any()) {
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| 100 | var targetValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndices).ToList();
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[5618] | 101 | var mean = targetValues.Average();
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| 102 | var range = targetValues.Max() - targetValues.Min();
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[5770] | 103 | EstimationLimits.Upper = mean + PunishmentFactor * range;
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| 104 | EstimationLimits.Lower = mean - PunishmentFactor * range;
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[6754] | 105 | } else {
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| 106 | EstimationLimits.Upper = double.MaxValue;
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| 107 | EstimationLimits.Lower = double.MinValue;
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[5618] | 108 | }
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| 109 | }
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[5623] | 110 |
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[5685] | 111 | protected override void OnProblemDataChanged() {
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| 112 | base.OnProblemDataChanged();
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| 113 | UpdateEstimationLimits();
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| 114 | }
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| 115 |
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| 116 | protected override void ParameterizeOperators() {
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| 117 | base.ParameterizeOperators();
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[5770] | 118 | if (Parameters.ContainsKey(EstimationLimitsParameterName)) {
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| 119 | var operators = Parameters.OfType<IValueParameter>().Select(p => p.Value).OfType<IOperator>().Union(Operators);
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| 120 | foreach (var op in operators.OfType<ISymbolicDataAnalysisBoundedOperator>()) {
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| 121 | op.EstimationLimitsParameter.ActualName = EstimationLimitsParameter.Name;
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| 122 | }
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[5685] | 123 | }
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| 124 | }
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[5618] | 125 | }
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| 126 | }
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