source: trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectivePearsonRSquaredEvaluator.cs @ 7259

Last change on this file since 7259 was 7259, checked in by swagner, 11 years ago

Updated year of copyrights to 2012 (#1716)

File size: 4.0 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2012 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
29namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Classification {
30  [Item("Pearson R² evaluator", "Calculates the square of the pearson correlation coefficient (also known as coefficient of determination) of a symbolic classification solution.")]
31  [StorableClass]
32  public class SymbolicClassificationSingleObjectivePearsonRSquaredEvaluator : SymbolicClassificationSingleObjectiveEvaluator {
33    [StorableConstructor]
34    protected SymbolicClassificationSingleObjectivePearsonRSquaredEvaluator(bool deserializing) : base(deserializing) { }
35    protected SymbolicClassificationSingleObjectivePearsonRSquaredEvaluator(SymbolicClassificationSingleObjectivePearsonRSquaredEvaluator original, Cloner cloner)
36      : base(original, cloner) {
37    }
38    public override IDeepCloneable Clone(Cloner cloner) {
39      return new SymbolicClassificationSingleObjectivePearsonRSquaredEvaluator(this, cloner);
40    }
41
42    public SymbolicClassificationSingleObjectivePearsonRSquaredEvaluator() : base() { }
43
44    public override bool Maximization { get { return true; } }
45
46    public override IOperation Apply() {
47      IEnumerable<int> rows = GenerateRowsToEvaluate();
48      var solution = SymbolicExpressionTreeParameter.ActualValue;
49      double quality = Calculate(SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, solution, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper, ProblemDataParameter.ActualValue, rows);
50      QualityParameter.ActualValue = new DoubleValue(quality);
51      return base.Apply();
52    }
53
54    public static double Calculate(ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, ISymbolicExpressionTree solution, double lowerEstimationLimit, double upperEstimationLimit, IClassificationProblemData problemData, IEnumerable<int> rows) {
55      IEnumerable<double> estimatedValues = interpreter.GetSymbolicExpressionTreeValues(solution, problemData.Dataset, rows);
56      IEnumerable<double> originalValues = problemData.Dataset.GetDoubleValues(problemData.TargetVariable, rows);
57      OnlineCalculatorError errorState;
58      double r2 = OnlinePearsonsRSquaredCalculator.Calculate(estimatedValues, originalValues, out errorState);
59      if (errorState != OnlineCalculatorError.None) return 0.0;
60      else return r2;
61    }
62
63    public override double Evaluate(IExecutionContext context, ISymbolicExpressionTree tree, IClassificationProblemData problemData, IEnumerable<int> rows) {
64      SymbolicDataAnalysisTreeInterpreterParameter.ExecutionContext = context;
65      EstimationLimitsParameter.ExecutionContext = context;
66
67      double r2 = Calculate(SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, tree, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper, problemData, rows);
68
69      SymbolicDataAnalysisTreeInterpreterParameter.ExecutionContext = null;
70      EstimationLimitsParameter.ExecutionContext = null;
71
72      return r2;
73    }
74  }
75}
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