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source: branches/ClassificationEnsembleVoting/HeuristicLab.Problems.DataAnalysis/3.4/OnlineCalculators/OnlineAccuracyCalculator.cs @ 7559

Last change on this file since 7559 was 7259, checked in by swagner, 12 years ago

Updated year of copyrights to 2012 (#1716)

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;
24using HeuristicLab.Common;
25
26namespace HeuristicLab.Problems.DataAnalysis {
27  public class OnlineAccuracyCalculator : IOnlineCalculator {
28
29    private int correctlyClassified;
30    private int n;
31    public double Accuracy {
32      get {
33        return correctlyClassified / (double)n;
34      }
35    }
36
37    public OnlineAccuracyCalculator() {
38      Reset();
39    }
40
41    #region IOnlineCalculator Members
42    private OnlineCalculatorError errorState;
43    public OnlineCalculatorError ErrorState {
44      get { return errorState; }
45    }
46    public double Value {
47      get { return Accuracy; }
48    }
49    public void Reset() {
50      n = 0;
51      correctlyClassified = 0;
52      errorState = OnlineCalculatorError.InsufficientElementsAdded;
53    }
54
55    public void Add(double original, double estimated) {
56      // ignore cases where original is NaN completly
57      if (!double.IsNaN(original)) {
58        // increment number of observed samples
59        n++;
60        if (original.IsAlmost(estimated)) {
61          // original = estimated = +Inf counts as correctly classified
62          // original = estimated = -Inf counts as correctly classified
63          correctlyClassified++;
64        }
65        errorState = OnlineCalculatorError.None; // number of (non-NaN) samples >= 1
66      }
67    }
68    #endregion
69
70    public static double Calculate(IEnumerable<double> originalValues, IEnumerable<double> estimatedValues, out OnlineCalculatorError errorState) {
71      IEnumerator<double> originalEnumerator = originalValues.GetEnumerator();
72      IEnumerator<double> estimatedEnumerator = estimatedValues.GetEnumerator();
73      OnlineAccuracyCalculator accuracyCalculator = new OnlineAccuracyCalculator();
74
75      // always move forward both enumerators (do not use short-circuit evaluation!)
76      while (originalEnumerator.MoveNext() & estimatedEnumerator.MoveNext()) {
77        double original = originalEnumerator.Current;
78        double estimated = estimatedEnumerator.Current;
79        accuracyCalculator.Add(original, estimated);
80        if (accuracyCalculator.ErrorState != OnlineCalculatorError.None) break;
81      }
82
83      // check if both enumerators are at the end to make sure both enumerations have the same length
84      if (accuracyCalculator.ErrorState == OnlineCalculatorError.None &&
85          (estimatedEnumerator.MoveNext() || originalEnumerator.MoveNext())) {
86        throw new ArgumentException("Number of elements in originalValues and estimatedValues enumerations doesn't match.");
87      } else {
88        errorState = accuracyCalculator.ErrorState;
89        return accuracyCalculator.Accuracy;
90      }
91    }
92  }
93}
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