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source: branches/HL-3.2-MonoMigration/HeuristicLab.StructureIdentification/Evaluation/MeanAbsolutePercentageErrorEvaluator.cs @ 2171

Last change on this file since 2171 was 555, checked in by gkronber, 16 years ago

ignore samples where the original value is 0 to prevent division by zero and thus MAPE=infinite

File size: 2.7 KB
Line 
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;
29using HeuristicLab.Functions;
30using HeuristicLab.DataAnalysis;
31
32namespace HeuristicLab.StructureIdentification {
33  public class MeanAbsolutePercentageErrorEvaluator : GPEvaluatorBase {
34    private DoubleData mape;
35    public override string Description {
36      get {
37        return @"Evaluates 'FunctionTree' for all samples of 'Dataset' and calculates
38the 'mean absolute percentage error (scale invariant)' of estimated values vs. real values of 'TargetVariable'.";
39      }
40    }
41
42    public MeanAbsolutePercentageErrorEvaluator()
43      : base() {
44      AddVariableInfo(new VariableInfo("MAPE", "The mean absolute percentage error of the model", typeof(DoubleData), VariableKind.New));
45    }
46
47    public override IOperation Apply(IScope scope) {
48      mape = GetVariableValue<DoubleData>("MAPE", scope, false, false);
49      if(mape == null) {
50        mape = new DoubleData();
51        scope.AddVariable(new HeuristicLab.Core.Variable(scope.TranslateName("MAPE"), mape));
52      }
53
54      return base.Apply(scope);
55    }
56
57    public override void Evaluate(int start, int end) {
58      double errorsSum = 0.0;
59      int n = 0;
60      for(int sample = start; sample < end; sample++) {
61        double estimated = GetEstimatedValue(sample);
62        double original = GetOriginalValue(sample);
63        SetOriginalValue(sample, estimated);
64        if(!double.IsNaN(original) && !double.IsInfinity(original) && original!=0.0) {
65          double percent_error = Math.Abs((estimated - original) / original);
66          errorsSum += percent_error;
67          n++;
68        }
69      }
70      double quality = errorsSum / n;
71      if(double.IsNaN(quality) || double.IsInfinity(quality))
72        quality = double.MaxValue;
73      mape.Data = quality;
74    }
75  }
76}
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