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source: trunk/sources/HeuristicLab.Problems.DataAnalysis/3.3/Evaluators/SimpleMSEEvaluator.cs @ 3376

Last change on this file since 3376 was 3376, checked in by swagner, 14 years ago

Moved interfaces and classes for deep cloning from HeuristicLab.Core to HeuristicLab.Common (#975).

File size: 2.7 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.Common;
27using HeuristicLab.Core;
28using HeuristicLab.Data;
29
30namespace HeuristicLab.Problems.DataAnalysis.Evaluators {
31  public class SimpleMSEEvaluator : SimpleEvaluator {
32
33    public SimpleMSEEvaluator()
34      : base() {
35      QualityParameter.ActualName = "MeanSquaredError";
36    }
37
38    protected override double Apply(DoubleMatrix values) {
39      return Calculate(values);
40    }
41
42    public static double Calculate(IEnumerable<double> original, IEnumerable<double> estimated) {
43      double sse = 0.0;
44      int cnt = 0;
45      var originalEnumerator = original.GetEnumerator();
46      var estimatedEnumerator = estimated.GetEnumerator();
47      while (originalEnumerator.MoveNext() & estimatedEnumerator.MoveNext()) {
48        double e = estimatedEnumerator.Current;
49        double o = originalEnumerator.Current;
50        if (!double.IsNaN(e) && !double.IsInfinity(e) &&
51            !double.IsNaN(o) && !double.IsInfinity(o)) {
52          double error = e - o;
53          sse += error * error;
54          cnt++;
55        }
56      }
57      if (estimatedEnumerator.MoveNext() || originalEnumerator.MoveNext()) {
58        throw new ArgumentException("Number of elements in original and estimated enumeration doesn't match.");
59      } else if (cnt == 0) {
60        throw new ArgumentException("Mean squared errors is not defined for input vectors of NaN or Inf");
61      } else {
62        double mse = sse / cnt;
63        return mse;
64      }
65    }
66
67    public static double Calculate(DoubleMatrix values) {
68      var original = from row in Enumerable.Range(0, values.Rows)
69                     select values[row, ORIGINAL_INDEX];
70      var estimated = from row in Enumerable.Range(0, values.Rows)
71                      select values[row, ORIGINAL_INDEX];
72      return Calculate(original, estimated);
73    }
74  }
75}
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