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source: branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis/3.3/Evaluators/SimpleMSEEvaluator.cs @ 7370

Last change on this file since 7370 was 5275, checked in by gkronber, 14 years ago

Merged changes from trunk to data analysis exploration branch and added fractional distance metric evaluator. #1142

File size: 3.1 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 HeuristicLab.Common;
26using HeuristicLab.Core;
27using HeuristicLab.Data;
28using HeuristicLab.Parameters;
29using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
30
31namespace HeuristicLab.Problems.DataAnalysis.Evaluators {
32  public class SimpleMSEEvaluator : SimpleEvaluator {
33
34    public ILookupParameter<DoubleValue> MeanSquaredErrorParameter {
35      get { return (ILookupParameter<DoubleValue>)Parameters["MeanSquaredError"]; }
36    }
37
38    [StorableConstructor]
39    protected SimpleMSEEvaluator(bool deserializing) : base(deserializing) { }
40    protected SimpleMSEEvaluator(SimpleMSEEvaluator original, Cloner cloner)
41      : base(original, cloner) {
42    }
43    public override IDeepCloneable Clone(Cloner cloner) {
44      return new SimpleMSEEvaluator(this, cloner);
45    }
46    public SimpleMSEEvaluator() {
47      Parameters.Add(new LookupParameter<DoubleValue>("MeanSquaredError", "The mean squared error of estimated values."));
48    }
49
50    protected override void Apply(DoubleMatrix values) {
51      MeanSquaredErrorParameter.ActualValue = new DoubleValue(Calculate(values));
52    }
53
54    public static double Calculate(IEnumerable<double> original, IEnumerable<double> estimated) {
55      var onlineMseEvaluator = new OnlineMeanSquaredErrorEvaluator();
56      var originalEnumerator = original.GetEnumerator();
57      var estimatedEnumerator = estimated.GetEnumerator();
58      while (originalEnumerator.MoveNext() & estimatedEnumerator.MoveNext()) {
59        double e = estimatedEnumerator.Current;
60        double o = originalEnumerator.Current;
61        onlineMseEvaluator.Add(o, e);
62      }
63      if (estimatedEnumerator.MoveNext() || originalEnumerator.MoveNext()) {
64        throw new ArgumentException("Number of elements in original and estimated enumeration doesn't match.");
65      } else {
66        return onlineMseEvaluator.MeanSquaredError;
67      }
68    }
69
70    public static double Calculate(DoubleMatrix values) {
71      var original = from row in Enumerable.Range(0, values.Rows)
72                     select values[row, ORIGINAL_INDEX];
73      var estimated = from row in Enumerable.Range(0, values.Rows)
74                      select values[row, ESTIMATION_INDEX];
75      return Calculate(original, estimated);
76    }
77  }
78}
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