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source: tags/3.3.0/HeuristicLab.Problems.DataAnalysis/3.3/Evaluators/SimpleMeanAbsolutePercentageOfRangeErrorEvaluator.cs

Last change on this file was 3452, checked in by gkronber, 14 years ago

Included tracking of best of run solution (based on validation set) and calculation of MSE, R² and rel. Error on training and test sets. #938 (Data types and operators for regression problems)

File size: 3.3 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 System.Linq;
25using System.Text;
26using HeuristicLab.Core;
27using HeuristicLab.Common;
28using HeuristicLab.Data;
29using HeuristicLab.Parameters;
30
31namespace HeuristicLab.Problems.DataAnalysis.Evaluators {
32  public class SimpleMeanAbsolutePercentageOfRangeErrorEvaluator : SimpleEvaluator {
33
34    public ILookupParameter<PercentValue> AveragePercentageOfRangeErrorParameter {
35      get { return (ILookupParameter<PercentValue>)Parameters["AveragePercentageOfRangeError"]; }
36    }
37
38    public SimpleMeanAbsolutePercentageOfRangeErrorEvaluator() {
39      Parameters.Add(new LookupParameter<PercentValue>("AveragePercentageOfRangeError", "The average relative (percentage of range) error of estimated values."));
40    }
41
42    protected override void Apply(DoubleMatrix values) {
43      var original = from i in Enumerable.Range(0, values.Rows)
44                     select values[i, ORIGINAL_INDEX];
45      var estimated = from i in Enumerable.Range(0, values.Rows)
46                      select values[i, ESTIMATION_INDEX];
47      AveragePercentageOfRangeErrorParameter.ActualValue = new PercentValue(Calculate(original, estimated));
48    }
49
50    public static double Calculate(IEnumerable<double> original, IEnumerable<double> estimated) {
51      double errorsSum = 0.0;
52      int n = 0;
53      IList<double> originalList = original as IList<double>;
54      if (originalList == null) originalList = original.ToList();
55
56      double range = originalList.Max() - originalList.Min();
57      if (double.IsInfinity(range)) return double.MaxValue;
58      if (range.IsAlmost(0.0)) return double.MaxValue;
59
60
61      var originalEnumerator = original.GetEnumerator();
62      var estimatedEnumerator = estimated.GetEnumerator();
63      while (originalEnumerator.MoveNext() & estimatedEnumerator.MoveNext()) {
64        double e = estimatedEnumerator.Current;
65        double o = originalEnumerator.Current;
66
67        if (!double.IsNaN(e) && !double.IsInfinity(e) &&
68          !double.IsNaN(o) && !double.IsInfinity(o) && !o.IsAlmost(0.0)) {
69          double percent_error = Math.Abs((e - o) / range);
70          errorsSum += percent_error;
71          n++;
72        }
73      }
74      if (estimatedEnumerator.MoveNext() || originalEnumerator.MoveNext()) {
75        throw new ArgumentException("Number of elements in original and estimated enumeration doesn't match.");
76      } else if (n == 0) {
77        return double.MaxValue;
78      } else {
79        return errorsSum / n;
80      }
81    }
82  }
83}
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