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source: trunk/sources/HeuristicLab.Problems.DataAnalysis/3.3/Evaluators/SimpleNMSEEvaluator.cs @ 3462

Last change on this file since 3462 was 3462, checked in by gkronber, 14 years ago

Refactored symbolic expression tree encoding and problem classes for symbolic regression. #937 , #938

File size: 2.2 KB
RevLine 
[3452]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;
[2379]23using System.Collections.Generic;
24using System.Linq;
25using System.Text;
[3462]26using HeuristicLab.Common;
[2379]27using HeuristicLab.Core;
28using HeuristicLab.Data;
[3452]29using HeuristicLab.Parameters;
[2379]30
[3452]31namespace HeuristicLab.Problems.DataAnalysis.Evaluators {
32  public class SimpleNMSEEvaluator : SimpleEvaluator {
[2379]33
[3452]34    public ILookupParameter<DoubleValue> NormalizedMeanSquaredErrorParameter {
35      get { return (ILookupParameter<DoubleValue>)Parameters["NormalizedMeanSquaredError"]; }
[2379]36    }
[3452]37
38    public SimpleNMSEEvaluator() {
39      Parameters.Add(new LookupParameter<DoubleValue>("NormalizedMeanSquaredError", "The normalized mean squared error (divided by variance) of estimated values."));
[2379]40    }
41
[3452]42    protected override void Apply(DoubleMatrix values) {
43      var original = from i in Enumerable.Range(0, values.Rows)
44                     select values[i, ORIGINAL_INDEX];
45      var estimated = from i in Enumerable.Range(0, values.Rows)
46                      select values[i, ESTIMATION_INDEX];
47
48      NormalizedMeanSquaredErrorParameter.ActualValue = new DoubleValue(Calculate(original, estimated));
[2379]49    }
[3452]50
51    public static double Calculate(IEnumerable<double> original, IEnumerable<double> estimated) {
52      double mse = SimpleMSEEvaluator.Calculate(original, estimated);
53      return mse / original.Variance();
54    }
[2379]55  }
56}
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