source: branches/RegressionBenchmarks/HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis/3.4/SingleObjective/SymbolicTimeSeriesPrognosisSingleObjectiveProblem.cs @ 6968

Last change on this file since 6968 was 6968, checked in by sforsten, 11 years ago

#1669: First version which can automatically generate data for some problems from http://www.vanillamodeling.com/

File size: 5.9 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2011 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.Collections.Generic;
23using System.Linq;
24using HeuristicLab.Common;
25using HeuristicLab.Core;
26using HeuristicLab.Parameters;
27using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
28
29namespace HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis {
30  [Item("Symbolic Time-Series Prognosis Problem (single objective)", "Represents a single objective symbolic time-series prognosis problem.")]
31  [StorableClass]
32  [Creatable("Problems")]
33  public class SymbolicTimeSeriesPrognosisSingleObjectiveProblem : SymbolicDataAnalysisSingleObjectiveProblem<ITimeSeriesPrognosisProblemData, ISymbolicTimeSeriesPrognosisSingleObjectiveEvaluator, ISymbolicDataAnalysisSolutionCreator>, ITimeSeriesPrognosisProblem {
34    private const double PunishmentFactor = 10;
35    private const int InitialMaximumTreeDepth = 8;
36    private const int InitialMaximumTreeLength = 25;
37    private const string EstimationLimitsParameterName = "EstimationLimits";
38    private const string EstimationLimitsParameterDescription = "The limits for the estimated value that can be returned by the symbolic regression model.";
39
40    #region parameter properties
41    public IFixedValueParameter<DoubleLimit> EstimationLimitsParameter {
42      get { return (IFixedValueParameter<DoubleLimit>)Parameters[EstimationLimitsParameterName]; }
43    }
44    #endregion
45    #region properties
46    public DoubleLimit EstimationLimits {
47      get { return EstimationLimitsParameter.Value; }
48    }
49    #endregion
50    [StorableConstructor]
51    protected SymbolicTimeSeriesPrognosisSingleObjectiveProblem(bool deserializing) : base(deserializing) { }
52    protected SymbolicTimeSeriesPrognosisSingleObjectiveProblem(SymbolicTimeSeriesPrognosisSingleObjectiveProblem original, Cloner cloner) : base(original, cloner) { }
53    public override IDeepCloneable Clone(Cloner cloner) { return new SymbolicTimeSeriesPrognosisSingleObjectiveProblem(this, cloner); }
54
55    public SymbolicTimeSeriesPrognosisSingleObjectiveProblem()
56      : base(new TimeSeriesPrognosisProblemData(), new SymbolicTimeSeriesPrognosisSingleObjectivePearsonRSquaredEvaluator(), new SymbolicDataAnalysisExpressionTreeCreator()) {
57      Parameters.Add(new FixedValueParameter<DoubleLimit>(EstimationLimitsParameterName, EstimationLimitsParameterDescription));
58
59      EstimationLimitsParameter.Hidden = true;
60
61      Maximization.Value = true;
62      MaximumSymbolicExpressionTreeDepth.Value = InitialMaximumTreeDepth;
63      MaximumSymbolicExpressionTreeLength.Value = InitialMaximumTreeLength;
64
65      SymbolicExpressionTreeGrammarParameter.ValueChanged += (o, e) => ConfigureGrammarSymbols();
66
67      ConfigureGrammarSymbols();
68
69      InitializeOperators();
70      UpdateEstimationLimits();
71    }
72
73    private void ConfigureGrammarSymbols() {
74      var grammar = SymbolicExpressionTreeGrammar as TypeCoherentExpressionGrammar;
75      if (grammar != null) grammar.ConfigureAsDefaultTimeSeriesPrognosisGrammar();
76    }
77
78    private void InitializeOperators() {
79      Operators.Add(new SymbolicTimeSeriesPrognosisSingleObjectiveTrainingBestSolutionAnalyzer());
80      Operators.Add(new SymbolicTimeSeriesPrognosisSingleObjectiveValidationBestSolutionAnalyzer());
81      Operators.Add(new SymbolicTimeSeriesPrognosisSingleObjectiveOverfittingAnalyzer());
82      ParameterizeOperators();
83    }
84
85    private void UpdateEstimationLimits() {
86      if (ProblemData.TrainingIndizes.Any()) {
87        var targetValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndizes).ToList();
88        var mean = targetValues.Average();
89        var range = targetValues.Max() - targetValues.Min();
90        EstimationLimits.Upper = mean + PunishmentFactor * range;
91        EstimationLimits.Lower = mean - PunishmentFactor * range;
92      } else {
93        EstimationLimits.Upper = double.MaxValue;
94        EstimationLimits.Lower = double.MinValue;
95      }
96    }
97
98    protected override void OnProblemDataChanged() {
99      base.OnProblemDataChanged();
100      UpdateEstimationLimits();
101    }
102
103    protected override void ParameterizeOperators() {
104      base.ParameterizeOperators();
105      if (Parameters.ContainsKey(EstimationLimitsParameterName)) {
106        var operators = Parameters.OfType<IValueParameter>().Select(p => p.Value).OfType<IOperator>().Union(Operators);
107        foreach (var op in operators.OfType<ISymbolicDataAnalysisBoundedOperator>()) {
108          op.EstimationLimitsParameter.ActualName = EstimationLimitsParameter.Name;
109        }
110      }
111    }
112
113    public override void ImportProblemDataFromFile(string fileName) {
114      TimeSeriesPrognosisProblemData problemData = TimeSeriesPrognosisProblemData.ImportFromFile(fileName);
115      ProblemData = problemData;
116    }
117
118    public override void CreateProblemDataFromBenchmark(IDataAnalysisBenchmarkProblemDataGenerator benchmarkGenerator) {
119      throw new System.NotImplementedException();
120    }
121
122    public override IEnumerable<IDataAnalysisBenchmarkProblemDataGenerator> GetBenchmarkProblemDataGenerators() {
123      throw new System.NotImplementedException();
124    }
125  }
126}
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