source: branches/2974_Constants_Optimization/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/MultiObjective/SymbolicRegressionMultiObjectiveProblem.cs @ 17193

Last change on this file since 17193 was 17193, checked in by mkommend, 4 months ago

#2974: Merged trunk changes into branch.

File size: 6.3 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) Heuristic and Evolutionary Algorithms Laboratory (HEAL)
4 *
5 * This file is part of HeuristicLab.
6 *
7 * HeuristicLab is free software: you can redistribute it and/or modify
8 * it under the terms of the GNU General Public License as published by
9 * the Free Software Foundation, either version 3 of the License, or
10 * (at your option) any later version.
11 *
12 * HeuristicLab is distributed in the hope that it will be useful,
13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
15 * GNU General Public License for more details.
16 *
17 * You should have received a copy of the GNU General Public License
18 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
19 */
20#endregion
21
22using System.Linq;
23using HeuristicLab.Common;
24using HeuristicLab.Core;
25using HeuristicLab.Data;
26using HeuristicLab.Optimization;
27using HeuristicLab.Parameters;
28using HEAL.Attic;
29
30namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression {
31  [Item("Symbolic Regression Problem (multi-objective)", "Represents a multi objective symbolic regression problem.")]
32  [StorableType("4A8D3658-66B3-48B4-B983-D46409045DBE")]
33  [Creatable(CreatableAttribute.Categories.GeneticProgrammingProblems, Priority = 110)]
34  public class SymbolicRegressionMultiObjectiveProblem : SymbolicDataAnalysisMultiObjectiveProblem<IRegressionProblemData, ISymbolicRegressionMultiObjectiveEvaluator, ISymbolicDataAnalysisSolutionCreator>, IRegressionProblem {
35    private const double PunishmentFactor = 10;
36    private const int InitialMaximumTreeDepth = 8;
37    private const int InitialMaximumTreeLength = 25;
38    private const string EstimationLimitsParameterName = "EstimationLimits";
39    private const string EstimationLimitsParameterDescription = "The lower and upper limit for the estimated value that can be returned by the symbolic regression model.";
40
41    #region parameter properties
42    public IFixedValueParameter<DoubleLimit> EstimationLimitsParameter {
43      get { return (IFixedValueParameter<DoubleLimit>)Parameters[EstimationLimitsParameterName]; }
44    }
45    #endregion
46
47    #region properties
48    public DoubleLimit EstimationLimits {
49      get { return EstimationLimitsParameter.Value; }
50    }
51
52    #endregion
53
54    [StorableConstructor]
55    protected SymbolicRegressionMultiObjectiveProblem(StorableConstructorFlag _) : base(_) { }
56    protected SymbolicRegressionMultiObjectiveProblem(SymbolicRegressionMultiObjectiveProblem original, Cloner cloner)
57      : base(original, cloner) {
58      RegisterEventHandlers();
59    }
60    public override IDeepCloneable Clone(Cloner cloner) { return new SymbolicRegressionMultiObjectiveProblem(this, cloner); }
61
62    public SymbolicRegressionMultiObjectiveProblem()
63      : base(new RegressionProblemData(), new SymbolicRegressionMultiObjectivePearsonRSquaredTreeSizeEvaluator(), new SymbolicDataAnalysisExpressionTreeCreator()) {
64      Parameters.Add(new FixedValueParameter<DoubleLimit>(EstimationLimitsParameterName, EstimationLimitsParameterDescription));
65
66      EstimationLimitsParameter.Hidden = true;
67
68      ApplyLinearScalingParameter.Value.Value = true;
69      Maximization = new BoolArray(new bool[] { true, false });
70      MaximumSymbolicExpressionTreeDepth.Value = InitialMaximumTreeDepth;
71      MaximumSymbolicExpressionTreeLength.Value = InitialMaximumTreeLength;
72
73      RegisterEventHandlers();
74      ConfigureGrammarSymbols();
75      InitializeOperators();
76      UpdateEstimationLimits();
77    }
78
79    [StorableHook(HookType.AfterDeserialization)]
80    private void AfterDeserialization() {
81      RegisterEventHandlers();
82    }
83
84    private void RegisterEventHandlers() {
85      SymbolicExpressionTreeGrammarParameter.ValueChanged += (o, e) => ConfigureGrammarSymbols();
86    }
87
88    private void ConfigureGrammarSymbols() {
89      var grammar = SymbolicExpressionTreeGrammar as TypeCoherentExpressionGrammar;
90      if (grammar != null) grammar.ConfigureAsDefaultRegressionGrammar();
91    }
92
93    private void InitializeOperators() {
94      Operators.Add(new SymbolicRegressionMultiObjectiveTrainingBestSolutionAnalyzer());
95      Operators.Add(new SymbolicRegressionMultiObjectiveValidationBestSolutionAnalyzer());
96      Operators.Add(new SymbolicExpressionTreePhenotypicSimilarityCalculator());
97      Operators.Add(new SymbolicRegressionPhenotypicDiversityAnalyzer(Operators.OfType<SymbolicExpressionTreePhenotypicSimilarityCalculator>()));
98      ParameterizeOperators();
99    }
100
101    private void UpdateEstimationLimits() {
102      if (ProblemData.TrainingIndices.Any()) {
103        var targetValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndices).ToList();
104        var mean = targetValues.Average();
105        var range = targetValues.Max() - targetValues.Min();
106        EstimationLimits.Upper = mean + PunishmentFactor * range;
107        EstimationLimits.Lower = mean - PunishmentFactor * range;
108      } else {
109        EstimationLimits.Upper = double.MaxValue;
110        EstimationLimits.Lower = double.MinValue;
111      }
112    }
113
114    protected override void OnProblemDataChanged() {
115      base.OnProblemDataChanged();
116      UpdateEstimationLimits();
117    }
118
119    protected override void ParameterizeOperators() {
120      base.ParameterizeOperators();
121      if (Parameters.ContainsKey(EstimationLimitsParameterName)) {
122        var operators = Parameters.OfType<IValueParameter>().Select(p => p.Value).OfType<IOperator>().Union(Operators);
123        foreach (var op in operators.OfType<ISymbolicDataAnalysisBoundedOperator>()) {
124          op.EstimationLimitsParameter.ActualName = EstimationLimitsParameter.Name;
125        }
126      }
127
128      foreach (var op in Operators.OfType<ISolutionSimilarityCalculator>()) {
129        op.SolutionVariableName = SolutionCreator.SymbolicExpressionTreeParameter.ActualName;
130        op.QualityVariableName = Evaluator.QualitiesParameter.ActualName;
131
132        if (op is SymbolicExpressionTreePhenotypicSimilarityCalculator) {
133          var phenotypicSimilarityCalculator = (SymbolicExpressionTreePhenotypicSimilarityCalculator)op;
134          phenotypicSimilarityCalculator.ProblemData = ProblemData;
135          phenotypicSimilarityCalculator.Interpreter = SymbolicExpressionTreeInterpreter;
136        }
137      }
138    }
139  }
140}
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