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source: branches/2389-EpsLexicase/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/EpsLexicaseAnalyzer.cs @ 15946

Last change on this file since 15946 was 15946, checked in by gkronber, 5 years ago

#2389: added prototype implementation of semi-dynamic eps-lexicase selection

File size: 3.3 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2018 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;
23
24using System.Linq;
25using HeuristicLab.Common;
26using HeuristicLab.Core;
27using HeuristicLab.Data;             
28using HeuristicLab.Parameters;
29using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
30using HeuristicLab.Problems.DataAnalysis;
31 
32namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression {
33  /// <summary>
34  /// Analyzer to use in combination with eps-lexicase selection
35  /// </summary>
36  [Item("EpsLexicaseAnalyzer", "")]
37  [StorableClass]
38  public sealed class EpsLexicaseAnalyzer : SymbolicDataAnalysisSingleObjectiveAnalyzer {
39
40    [StorableConstructor]
41    private EpsLexicaseAnalyzer(bool deserializing) : base(deserializing) { }
42    private EpsLexicaseAnalyzer(EpsLexicaseAnalyzer original, Cloner cloner) : base(original, cloner) { }
43    public override IDeepCloneable Clone(Cloner cloner) {
44      return new EpsLexicaseAnalyzer(this, cloner);
45    }
46
47    public EpsLexicaseAnalyzer()
48      : base() {
49      Parameters.Add(new LookupParameter<IRegressionProblemData>("ProblemData"));
50      Parameters.Add(new LookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter>("SymbolicExpressionTreeInterpreter"));
51      Parameters.Add(new LookupParameter<DoubleLimit>("EstimationLimits"));
52      Parameters.Add(new ScopeTreeLookupParameter<DoubleArray>("Errors", 1));
53    }
54
55    public override IOperation Apply() {
56      var problemData = (IRegressionProblemData)Parameters["ProblemData"].ActualValue;
57      var ds = problemData.Dataset;
58      var trainingRows = problemData.TrainingIndices.ToArray();
59      var y = problemData.TargetVariableTrainingValues.ToArray();
60      var trees = SymbolicExpressionTree;
61      var interpreter = (ISymbolicDataAnalysisExpressionTreeInterpreter)Parameters["SymbolicExpressionTreeInterpreter"].ActualValue;
62      var limits = (DoubleLimit)Parameters["EstimationLimits"].ActualValue;
63
64      var errors = new ItemArray<DoubleArray>(trees.Length);
65      int i = 0;
66      foreach (var tree in trees) {
67        var model = new SymbolicRegressionModel(problemData.TargetVariable, tree, (ISymbolicDataAnalysisExpressionTreeInterpreter)interpreter.Clone(), limits.Lower, limits.Upper);
68        if (ApplyLinearScalingParameter.ActualValue.Value)
69          model.Scale(problemData);
70
71        errors[i] = new DoubleArray(y.Zip(model.GetEstimatedValues(ds, trainingRows), (yi, pi) => Math.Abs(yi - pi)).ToArray());
72        i++;
73      }
74      Parameters["Errors"].ActualValue = errors;
75
76      return base.Apply();
77    }
78  }
79}
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