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

Last change on this file since 3996 was 3996, checked in by gkronber, 11 years ago

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

File size: 2.0 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 OnlineMeanSquaredErrorEvaluator : IOnlineEvaluator {
33
34    private double sse;
35    private int n;
36    public double MeanSquaredError {
37      get {
38        if (n < 1)
39          throw new InvalidOperationException("No elements");
40        else
41          return sse / n;
42      }
43    }
44
45    public OnlineMeanSquaredErrorEvaluator() {
46      Reset();
47    }
48
49    #region IOnlineEvaluator Members
50    public void Reset() {
51      n = 0;
52      sse = 0.0;
53    }
54
55    public void Add(double original, double estimated) {
56      if (double.IsNaN(estimated) || double.IsInfinity(estimated) ||
57          double.IsNaN(original) || double.IsInfinity(original)) {
58            throw new ArgumentException("Mean squared error is not defined for NaN or infinity elements");
59      } else {
60        double error = estimated - original;
61        sse += error * error;
62        n++;
63      }
64    }
65    #endregion
66  }
67}
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