source: trunk/sources/HeuristicLab.Problems.DataAnalysis/3.3/Evaluators/OnlineNormalizedMeanSquaredErrorEvaluator.cs @ 4022

Last change on this file since 4022 was 4022, checked in by gkronber, 11 years ago

Worked on symbolic regression classes to prepare for time series prognosis plugin. #1081

File size: 2.4 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 OnlineNormalizedMeanSquaredErrorEvaluator : IOnlineEvaluator {
33    private OnlineMeanAndVarianceCalculator meanSquaredErrorCalculator;
34    private OnlineMeanAndVarianceCalculator originalVarianceCalculator;
35
36    public double NormalizedMeanSquaredError {
37      get {
38        return meanSquaredErrorCalculator.Mean / originalVarianceCalculator.Variance;
39      }
40    }
41
42    public OnlineNormalizedMeanSquaredErrorEvaluator() {
43      meanSquaredErrorCalculator = new OnlineMeanAndVarianceCalculator();
44      originalVarianceCalculator = new OnlineMeanAndVarianceCalculator();
45      Reset();
46    }
47
48    #region IOnlineEvaluator Members
49    public double Value {
50      get { return NormalizedMeanSquaredError; }
51    }
52
53    public void Reset() {
54      meanSquaredErrorCalculator.Reset();
55      originalVarianceCalculator.Reset();
56    }
57
58    public void Add(double original, double estimated) {
59      if (double.IsNaN(estimated) || double.IsInfinity(estimated) ||
60          double.IsNaN(original) || double.IsInfinity(original)) {
61        throw new ArgumentException("Mean squared error is not defined for NaN or infinity elements");
62      } else {
63        double error = estimated - original;
64        meanSquaredErrorCalculator.Add(error * error);
65        originalVarianceCalculator.Add(original);
66      }
67    }
68    #endregion
69  }
70}
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