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source: trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/OnlineEvaluators/OnlineMeanSquaredErrorEvaluator.cs @ 5894

Last change on this file since 5894 was 5894, checked in by gkronber, 13 years ago

#1453: Added an ErrorState property to online evaluators to indicate if the result value is valid or if there has been an error in the calculation. Adapted all classes that use one of the online evaluators to check this property.

File size: 3.2 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2011 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;
24
25namespace HeuristicLab.Problems.DataAnalysis {
26  public class OnlineMeanSquaredErrorEvaluator : IOnlineEvaluator {
27
28    private double sse;
29    private int n;
30    public double MeanSquaredError {
31      get {
32        return n > 0 ? sse / n : 0.0;
33      }
34    }
35
36    public OnlineMeanSquaredErrorEvaluator() {
37      Reset();
38    }
39
40    #region IOnlineEvaluator Members
41    private OnlineEvaluatorError errorState;
42    public OnlineEvaluatorError ErrorState {
43      get { return errorState; }
44    }
45    public double Value {
46      get { return MeanSquaredError; }
47    }
48    public void Reset() {
49      n = 0;
50      sse = 0.0;
51      errorState = OnlineEvaluatorError.InsufficientElementsAdded;
52    }
53
54    public void Add(double original, double estimated) {
55      if (double.IsNaN(estimated) || double.IsInfinity(estimated) ||
56          double.IsNaN(original) || double.IsInfinity(original)) {
57        errorState = errorState | OnlineEvaluatorError.InvalidValueAdded;
58      } else if (!errorState.HasFlag(OnlineEvaluatorError.InvalidValueAdded)) {
59        double error = estimated - original;
60        sse += error * error;
61        n++;
62        errorState = OnlineEvaluatorError.None; // n >= 1
63      }
64    }
65    #endregion
66
67    public static double Calculate(IEnumerable<double> first, IEnumerable<double> second, out OnlineEvaluatorError errorState) {
68      IEnumerator<double> firstEnumerator = first.GetEnumerator();
69      IEnumerator<double> secondEnumerator = second.GetEnumerator();
70      OnlineMeanSquaredErrorEvaluator mseEvaluator = new OnlineMeanSquaredErrorEvaluator();
71
72      // always move forward both enumerators (do not use short-circuit evaluation!)
73      while (firstEnumerator.MoveNext() & secondEnumerator.MoveNext()) {
74        double estimated = secondEnumerator.Current;
75        double original = firstEnumerator.Current;
76        mseEvaluator.Add(original, estimated);
77      }
78
79      // check if both enumerators are at the end to make sure both enumerations have the same length
80      if (secondEnumerator.MoveNext() || firstEnumerator.MoveNext()) {
81        throw new ArgumentException("Number of elements in first and second enumeration doesn't match.");
82      } else {
83        errorState = mseEvaluator.ErrorState;
84        return mseEvaluator.MeanSquaredError;
85      }
86    }
87  }
88}
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