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source: branches/1776_ClassificationEnsembleVoting/HeuristicLab.Problems.DataAnalysis/3.4/OnlineCalculators/OnlineMaxAbsoluteErrorCalculator.cs

Last change on this file was 7866, checked in by sforsten, 13 years ago

#1776:

  • merged r7454:7863 trunk into branch to make it compatible again
  • adjusted GetConfidence of MajorityVoteWeightCalculator to be in an interval of [0, 1]
File size: 3.5 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2012 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 OnlineMaxAbsoluteErrorCalculator : IOnlineCalculator {
27
28    private double mae;
29    private int n;
30    public double MaxAbsoluteError {
31      get {
32        return n > 0 ? mae : 0.0;
33      }
34    }
35
36    public OnlineMaxAbsoluteErrorCalculator() {
37      Reset();
38    }
39
40    #region IOnlineCalculator Members
41    private OnlineCalculatorError errorState;
42    public OnlineCalculatorError ErrorState {
43      get { return errorState; }
44    }
45    public double Value {
46      get { return MaxAbsoluteError; }
47    }
48    public void Reset() {
49      n = 0;
50      mae = double.MinValue;
51      errorState = OnlineCalculatorError.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) || (errorState & OnlineCalculatorError.InvalidValueAdded) > 0) {
57        errorState = errorState | OnlineCalculatorError.InvalidValueAdded;
58      } else {
59        double error = Math.Abs(estimated - original);
60        if (error > mae)
61          mae = error;
62        n++;
63        errorState = errorState & (~OnlineCalculatorError.InsufficientElementsAdded);        // n >= 1
64      }
65    }
66    #endregion
67
68    public static double Calculate(IEnumerable<double> originalValues, IEnumerable<double> estimatedValues, out OnlineCalculatorError errorState) {
69      IEnumerator<double> originalEnumerator = originalValues.GetEnumerator();
70      IEnumerator<double> estimatedEnumerator = estimatedValues.GetEnumerator();
71      OnlineMaxAbsoluteErrorCalculator maeCalculator = new OnlineMaxAbsoluteErrorCalculator();
72
73      // always move forward both enumerators (do not use short-circuit evaluation!)
74      while (originalEnumerator.MoveNext() & estimatedEnumerator.MoveNext()) {
75        double original = originalEnumerator.Current;
76        double estimated = estimatedEnumerator.Current;
77        maeCalculator.Add(original, estimated);
78        if (maeCalculator.ErrorState != OnlineCalculatorError.None) break;
79      }
80
81      // check if both enumerators are at the end to make sure both enumerations have the same length
82      if (maeCalculator.ErrorState == OnlineCalculatorError.None &&
83         (estimatedEnumerator.MoveNext() || originalEnumerator.MoveNext())) {
84        throw new ArgumentException("Number of elements in originalValues and estimatedValues enumerations doesn't match.");
85      } else {
86        errorState = maeCalculator.ErrorState;
87        return maeCalculator.MaxAbsoluteError;
88      }
89    }
90  }
91}
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