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source: branches/GP.Grammar.Editor/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectivePearsonRSquaredEvaluator.cs @ 6934

Last change on this file since 6934 was 6784, checked in by mkommend, 13 years ago

#1479: Integrated trunk changes.

File size: 4.0 KB
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[5500]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 HeuristicLab.Common;
24using HeuristicLab.Core;
25using HeuristicLab.Data;
26using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
27using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
28
[5501]29namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression {
[5618]30  [Item("Pearson R² Evaluator", "Calculates the square of the pearson correlation coefficient (also known as coefficient of determination) of a symbolic regression solution.")]
[5500]31  [StorableClass]
32  public class SymbolicRegressionSingleObjectivePearsonRSquaredEvaluator : SymbolicRegressionSingleObjectiveEvaluator {
33    [StorableConstructor]
34    protected SymbolicRegressionSingleObjectivePearsonRSquaredEvaluator(bool deserializing) : base(deserializing) { }
35    protected SymbolicRegressionSingleObjectivePearsonRSquaredEvaluator(SymbolicRegressionSingleObjectivePearsonRSquaredEvaluator original, Cloner cloner)
36      : base(original, cloner) {
37    }
38    public override IDeepCloneable Clone(Cloner cloner) {
39      return new SymbolicRegressionSingleObjectivePearsonRSquaredEvaluator(this, cloner);
40    }
41
[5505]42    public SymbolicRegressionSingleObjectivePearsonRSquaredEvaluator() : base() { }
43
[5514]44    public override bool Maximization { get { return true; } }
45
[5500]46    public override IOperation Apply() {
[5851]47      var solution = SymbolicExpressionTreeParameter.ActualValue;
[5500]48      IEnumerable<int> rows = GenerateRowsToEvaluate();
[5851]49
50      double quality = Calculate(SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, solution, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper, ProblemDataParameter.ActualValue, rows);
51      QualityParameter.ActualValue = new DoubleValue(quality);
52
[5500]53      return base.Apply();
54    }
55
[5624]56    public static double Calculate(ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, ISymbolicExpressionTree solution, double lowerEstimationLimit, double upperEstimationLimit, IRegressionProblemData problemData, IEnumerable<int> rows) {
[5500]57      IEnumerable<double> estimatedValues = interpreter.GetSymbolicExpressionTreeValues(solution, problemData.Dataset, rows);
[6784]58      IEnumerable<double> originalValues = problemData.Dataset.GetDoubleValues(problemData.TargetVariable, rows);
[5942]59      OnlineCalculatorError errorState;
60      double r2 = OnlinePearsonsRSquaredCalculator.Calculate(estimatedValues, originalValues, out errorState);
61      if (errorState != OnlineCalculatorError.None) return 0.0;
[5894]62      else return r2;
[5500]63    }
[5613]64
65    public override double Evaluate(IExecutionContext context, ISymbolicExpressionTree tree, IRegressionProblemData problemData, IEnumerable<int> rows) {
[5722]66      SymbolicDataAnalysisTreeInterpreterParameter.ExecutionContext = context;
[5770]67      EstimationLimitsParameter.ExecutionContext = context;
[5722]68
[5770]69      double r2 = Calculate(SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, tree, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper, problemData, rows);
[5722]70
71      SymbolicDataAnalysisTreeInterpreterParameter.ExecutionContext = null;
[5770]72      EstimationLimitsParameter.ExecutionContext = null;
[5722]73
74      return r2;
[5613]75    }
[5500]76  }
77}
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