Free cookie consent management tool by TermsFeed Policy Generator

source: branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/Evaluators/SymbolicRegressionPearsonsRSquaredEvaluator.cs @ 4202

Last change on this file since 4202 was 4202, checked in by gkronber, 14 years ago

Changed R² evaluator to return 0 when the estimated values contain NaN values. #1142.

File size: 3.4 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2010 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.Core;
25using HeuristicLab.Data;
26using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
27using HeuristicLab.Parameters;
28using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
29using HeuristicLab.Problems.DataAnalysis.Evaluators;
30using HeuristicLab.Problems.DataAnalysis.Symbolic;
31
32namespace HeuristicLab.Problems.DataAnalysis.Regression.Symbolic {
33  [Item("SymbolicRegressionPearsonsRSquaredEvaluator", "Calculates the pearson r² correlation coefficient of a symbolic regression solution.")]
34  [StorableClass]
35  public class SymbolicRegressionPearsonsRSquaredEvaluator : SingleObjectiveSymbolicRegressionEvaluator {
36    public SymbolicRegressionPearsonsRSquaredEvaluator()
37      : base() {
38    }
39
40    public override double Evaluate(ISymbolicExpressionTreeInterpreter interpreter, SymbolicExpressionTree solution, double lowerEstimationLimit, double upperEstimationLimit, Dataset dataset, string targetVariable, IEnumerable<int> rows) {
41      double mse = Calculate(interpreter, solution, lowerEstimationLimit, upperEstimationLimit, dataset, targetVariable, rows);
42      return mse;
43    }
44
45    public static double Calculate(ISymbolicExpressionTreeInterpreter interpreter, SymbolicExpressionTree solution, double lowerEstimationLimit, double upperEstimationLimit, Dataset dataset, string targetVariable, IEnumerable<int> rows) {
46      IEnumerable<double> estimatedValues = interpreter.GetSymbolicExpressionTreeValues(solution, dataset, rows);
47      IEnumerable<double> originalValues = dataset.GetEnumeratedVariableValues(targetVariable, rows);
48      IEnumerator<double> originalEnumerator = originalValues.GetEnumerator();
49      IEnumerator<double> estimatedEnumerator = estimatedValues.GetEnumerator();
50      OnlinePearsonsRSquaredEvaluator r2Evaluator = new OnlinePearsonsRSquaredEvaluator();
51
52      while (originalEnumerator.MoveNext() & estimatedEnumerator.MoveNext()) {
53        double estimated = estimatedEnumerator.Current;
54        double original = originalEnumerator.Current;
55        if (double.IsNaN(estimated))
56          return 0.0;
57        else
58          estimated = Math.Min(upperEstimationLimit, Math.Max(lowerEstimationLimit, estimated));
59        r2Evaluator.Add(original, estimated);
60      }
61
62      if (estimatedEnumerator.MoveNext() || originalEnumerator.MoveNext()) {
63        throw new ArgumentException("Number of elements in original and estimated enumeration doesn't match.");
64      } else {
65        return r2Evaluator.RSquared;
66      }
67    }
68  }
69}
Note: See TracBrowser for help on using the repository browser.