source: trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SymbolicRegressionPruningOperator.cs @ 11026

Last change on this file since 11026 was 11026, checked in by bburlacu, 6 years ago

#2143:

  • Removed ToArray() calls from SymbolicClassificationPruningOperator.cs and SymbolicRegressionPruningOperator.cs.
  • Changed UpdateCounter, UpdateInterval, PruningProbability, PopulationSliceParameter to FixedValueParameters in SymbolicDataAnalysisSingleObjectivePruningAnalyzer.cs.
  • Removed empty operator data member
  • Added parameter descriptions
  • Improved source organization
File size: 3.2 KB
Line 
1#region License Information
2
3/* HeuristicLab
4 * Copyright (C) 2002-2014 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
5 *
6 * This file is part of HeuristicLab.
7 *
8 * HeuristicLab is free software: you can redistribute it and/or modify
9 * it under the terms of the GNU General Public License as published by
10 * the Free Software Foundation, either version 3 of the License, or
11 * (at your option) any later version.
12 *
13 * HeuristicLab is distributed in the hope that it will be useful,
14 * but WITHOUT ANY WARRANTY; without even the implied warranty of
15 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
16 * GNU General Public License for more details.
17 *
18 * You should have received a copy of the GNU General Public License
19 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
20 */
21
22#endregion
23
24using System.Linq;
25using HeuristicLab.Common;
26using HeuristicLab.Core;
27using HeuristicLab.Parameters;
28using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
29
30namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression {
31  [StorableClass]
32  [Item("SymbolicRegressionPruningOperator", "An operator which prunes symbolic regression trees.")]
33  public class SymbolicRegressionPruningOperator : SymbolicDataAnalysisExpressionPruningOperator {
34    private const string ImpactValuesCalculatorParameterName = "ImpactValuesCalculator";
35
36    protected SymbolicRegressionPruningOperator(SymbolicRegressionPruningOperator original, Cloner cloner)
37      : base(original, cloner) {
38    }
39    public override IDeepCloneable Clone(Cloner cloner) {
40      return new SymbolicRegressionPruningOperator(this, cloner);
41    }
42
43    [StorableConstructor]
44    protected SymbolicRegressionPruningOperator(bool deserializing) : base(deserializing) { }
45
46    public SymbolicRegressionPruningOperator() {
47      var impactValuesCalculator = new SymbolicRegressionSolutionImpactValuesCalculator();
48      Parameters.Add(new ValueParameter<ISymbolicDataAnalysisSolutionImpactValuesCalculator>(ImpactValuesCalculatorParameterName, "The impact values calculator to be used for figuring out the node impacts.", impactValuesCalculator));
49    }
50
51    protected override ISymbolicDataAnalysisModel CreateModel() {
52      return new SymbolicRegressionModel(SymbolicExpressionTree, Interpreter, EstimationLimits.Lower, EstimationLimits.Upper);
53    }
54
55    protected override double Evaluate(IDataAnalysisModel model) {
56      var regressionModel = (IRegressionModel)model;
57      var regressionProblemData = (IRegressionProblemData)ProblemData;
58      var trainingIndices = Enumerable.Range(FitnessCalculationPartition.Start, FitnessCalculationPartition.Size);
59      var estimatedValues = regressionModel.GetEstimatedValues(ProblemData.Dataset, trainingIndices); // also bounds the values
60      var targetValues = ProblemData.Dataset.GetDoubleValues(regressionProblemData.TargetVariable, trainingIndices);
61      OnlineCalculatorError errorState;
62      var quality = OnlinePearsonsRSquaredCalculator.Calculate(targetValues, estimatedValues, out errorState);
63      if (errorState != OnlineCalculatorError.None) return double.NaN;
64      return quality;
65    }
66  }
67}
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