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source: trunk/sources/HeuristicLab.Problems.DataAnalysis/3.3/Evaluators/SimpleMSEEvaluator.cs @ 3996

Last change on this file since 3996 was 3996, checked in by gkronber, 14 years ago

Improved efficiency of analyzers and evaluators for regression problems. #1074

File size: 2.8 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;
29using HeuristicLab.Parameters;
30
31namespace HeuristicLab.Problems.DataAnalysis.Evaluators {
32  public class SimpleMSEEvaluator : SimpleEvaluator {
33
34    public ILookupParameter<DoubleValue> MeanSquaredErrorParameter {
35      get { return (ILookupParameter<DoubleValue>)Parameters["MeanSquaredError"]; }
36    }
37
38    public SimpleMSEEvaluator() {
39      Parameters.Add(new LookupParameter<DoubleValue>("MeanSquaredError", "The mean squared error of estimated values."));
40    }
41
42    protected override void Apply(DoubleMatrix values) {
43      MeanSquaredErrorParameter.ActualValue = new DoubleValue(Calculate(values));
44    }
45
46    public static double Calculate(IEnumerable<double> original, IEnumerable<double> estimated) {
47      var onlineMseEvaluator = new OnlineMeanSquaredErrorEvaluator();
48      var originalEnumerator = original.GetEnumerator();
49      var estimatedEnumerator = estimated.GetEnumerator();
50      while (originalEnumerator.MoveNext() & estimatedEnumerator.MoveNext()) {
51        double e = estimatedEnumerator.Current;
52        double o = originalEnumerator.Current;
53        onlineMseEvaluator.Add(o, e);
54      }
55      if (estimatedEnumerator.MoveNext() || originalEnumerator.MoveNext()) {
56        throw new ArgumentException("Number of elements in original and estimated enumeration doesn't match.");
57      } else {
58        return onlineMseEvaluator.MeanSquaredError;
59      }
60    }
61
62    public static double Calculate(DoubleMatrix values) {
63      var original = from row in Enumerable.Range(0, values.Rows)
64                     select values[row, ORIGINAL_INDEX];
65      var estimated = from row in Enumerable.Range(0, values.Rows)
66                      select values[row, ESTIMATION_INDEX];
67      return Calculate(original, estimated);
68    }
69  }
70}
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