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source: trunk/sources/HeuristicLab.GP.StructureIdentification/Evaluators/CoefficientOfDeterminationEvaluator.cs @ 885

Last change on this file since 885 was 712, checked in by gkronber, 16 years ago

fixed a stupid mistake introduced with r702 #328 (GP evaluation doesn't work in a thread parallel engine).

File size: 3.1 KB
RevLine 
[645]1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2008 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 System.Linq;
25using System.Text;
26using HeuristicLab.Core;
27using HeuristicLab.Data;
28using HeuristicLab.Operators;
29
30namespace HeuristicLab.GP.StructureIdentification {
31  public class CoefficientOfDeterminationEvaluator : GPEvaluatorBase {
32    public override string Description {
33      get {
34        return @"Evaluates 'FunctionTree' for all samples of 'Dataset' and calculates
35the 'coefficient of determination' of estimated values vs. real values of 'TargetVariable'.";
36      }
37    }
38
39    public CoefficientOfDeterminationEvaluator()
40      : base() {
41      AddVariableInfo(new VariableInfo("R2", "The coefficient of determination of the model", typeof(DoubleData), VariableKind.New));
42    }
43
[702]44    public override void Evaluate(IScope scope, BakedTreeEvaluator evaluator, HeuristicLab.DataAnalysis.Dataset dataset, int targetVariable, int start, int end, bool updateTargetValues) {
[645]45      double errorsSquaredSum = 0.0;
46      double originalDeviationTotalSumOfSquares = 0.0;
[702]47      double targetMean = dataset.GetMean(targetVariable, start, end);
[712]48      for (int sample = start; sample < end; sample++) {
[702]49        double estimated = evaluator.Evaluate(sample);
[712]50        double original = dataset.GetValue(sample, targetVariable);
51        if (updateTargetValues) {
52          dataset.SetValue(sample, targetVariable, estimated);
[702]53        }
[712]54        if (!double.IsNaN(original) && !double.IsInfinity(original)) {
[645]55          double error = estimated - original;
56          errorsSquaredSum += error * error;
57
[702]58          double origDeviation = original - targetMean;
[645]59          originalDeviationTotalSumOfSquares += origDeviation * origDeviation;
60        }
61      }
62
63      double quality = 1 - errorsSquaredSum / originalDeviationTotalSumOfSquares;
[712]64      if (quality > 1)
[645]65        throw new InvalidProgramException();
[712]66      if (double.IsNaN(quality) || double.IsInfinity(quality))
[645]67        quality = double.MaxValue;
[702]68
69      DoubleData r2 = GetVariableValue<DoubleData>("R2", scope, false, false);
[712]70      if (r2 == null) {
[702]71        r2 = new DoubleData();
72        scope.AddVariable(new HeuristicLab.Core.Variable(scope.TranslateName("R2"), r2));
73      }
74
[645]75      r2.Data = quality;
76    }
77  }
78}
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