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source: branches/CEDMA-Exporter-715/sources/HeuristicLab.GP.StructureIdentification.ConditionalEvaluation/3.3/ConditionalVarianceAccountedForEvaluator.cs @ 3199

Last change on this file since 3199 was 2136, checked in by gkronber, 15 years ago

Improved handling of exceptional cases in data-based modeling evaluators. #688 (SimpleEvaluators should handle exceptional cases more gracefully)

File size: 2.2 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2008 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.Core;
27using HeuristicLab.Data;
28using HeuristicLab.DataAnalysis;
29using HeuristicLab.Modeling;
30
31namespace HeuristicLab.GP.StructureIdentification.ConditionalEvaluation {
32  /// <summary>
33  /// The Variance Accounted For (VAF) function calculates is computed as
34  /// VAF(y,y') = ( 1 - var(y-y')/var(y) )
35  /// where y' denotes the predicted / modelled values for y and var(x) the variance of a signal x.
36  /// </summary>
37  public class ConditionalVarianceAccountedForEvaluator : ConditionalEvaluatorBase {
38    public override string OutputVariableName {
39      get {
40        return "VAF";
41      }
42    }
43    public override string Description {
44      get {
45        return @"Evaluates 'FunctionTree' for all samples of 'DataSet' and calculates
46the variance-accounted-for quality measure for the estimated values vs. the real values of 'TargetVariable'.
47
48The Variance Accounted For (VAF) function is computed as
49VAF(y,y') = ( 1 - var(y-y')/var(y) )
50where y' denotes the predicted / modelled values for y and var(x) the variance of a signal x.";
51      }
52    }
53
54    public override double Evaluate(double[,] values) {
55      try { return SimpleVarianceAccountedForEvaluator.Calculate(values); }
56      catch (ArgumentException) {
57        return double.NegativeInfinity;
58      }
59    }
60  }
61}
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