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source: trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectivePearsonRSquaredEvaluator.cs @ 5823

Last change on this file since 5823 was 5823, checked in by gkronber, 13 years ago

#1418 fixed minor issues in symbolic data analysis classes.

File size: 4.1 KB
Line 
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;
23using System.Collections.Generic;
24using HeuristicLab.Common;
25using HeuristicLab.Core;
26using HeuristicLab.Data;
27using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
28using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
29
30namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Classification {
31  [Item("Pearson R² evaluator", "Calculates the square of the pearson correlation coefficient (also known as coefficient of determination) of a symbolic classification solution.")]
32  [StorableClass]
33  public class SymbolicClassificationSingleObjectivePearsonRSquaredEvaluator : SymbolicClassificationSingleObjectiveEvaluator {
34    [StorableConstructor]
35    protected SymbolicClassificationSingleObjectivePearsonRSquaredEvaluator(bool deserializing) : base(deserializing) { }
36    protected SymbolicClassificationSingleObjectivePearsonRSquaredEvaluator(SymbolicClassificationSingleObjectivePearsonRSquaredEvaluator original, Cloner cloner)
37      : base(original, cloner) {
38    }
39    public override IDeepCloneable Clone(Cloner cloner) {
40      return new SymbolicClassificationSingleObjectivePearsonRSquaredEvaluator(this, cloner);
41    }
42
43    public SymbolicClassificationSingleObjectivePearsonRSquaredEvaluator() : base() { }
44
45    public override bool Maximization { get { return true; } }
46
47    public override IOperation Apply() {
48      IEnumerable<int> rows = GenerateRowsToEvaluate();
49      double quality = Calculate(SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, SymbolicExpressionTreeParameter.ActualValue, 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.GetEnumeratedVariableValues(problemData.TargetVariable, rows);
57      try {
58        return OnlinePearsonsRSquaredEvaluator.Calculate(originalValues, estimatedValues);
59      }
60      catch (ArgumentException) {
61        // if R² cannot be calculated because of NaN or ininity elements => return worst possible fitness value
62        return 0.0;
63      }
64    }
65
66    public override double Evaluate(IExecutionContext context, ISymbolicExpressionTree tree, IClassificationProblemData problemData, IEnumerable<int> rows) {
67      SymbolicDataAnalysisTreeInterpreterParameter.ExecutionContext = context;
68      EstimationLimitsParameter.ExecutionContext = context;
69
70      double r2 = Calculate(SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, tree, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper, problemData, rows);
71
72      SymbolicDataAnalysisTreeInterpreterParameter.ExecutionContext = null;
73      EstimationLimitsParameter.ExecutionContext = null;
74
75      return r2;
76    }
77  }
78}
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