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source: branches/HL-3.2-MonoMigration/HeuristicLab.StructureIdentification/Evaluation/TheilInequalityCoefficientEvaluator.cs @ 3494

Last change on this file since 3494 was 482, checked in by gkronber, 16 years ago

made a few more improvements in the GP evaluators (ticket #242 All GP evaluators should support the 'UseEstimatedTargetValues' switch for autoregressive modelling)

File size: 3.7 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.Operators;
29using HeuristicLab.Functions;
30using HeuristicLab.DataAnalysis;
31
32namespace HeuristicLab.StructureIdentification {
33  public class TheilInequalityCoefficientEvaluator : GPEvaluatorBase {
34    private bool differential;
35    private DoubleData theilInequaliy;
36    public override string Description {
37      get {
38        return @"Evaluates 'FunctionTree' for all samples of 'Dataset' and calculates
39the 'Theil inequality coefficient (scale invariant)' of estimated values vs. real values of 'TargetVariable'.";
40      }
41    }
42
43    public TheilInequalityCoefficientEvaluator()
44      : base() {
45      AddVariableInfo(new VariableInfo("Differential", "Wether to calculate the coefficient for the predicted change vs. original change or for the absolute prediction vs. original value", typeof(BoolData), VariableKind.In));
46      AddVariableInfo(new VariableInfo("TheilInequalityCoefficient", "Theil's inequality coefficient of the model", typeof(DoubleData), VariableKind.New));
47
48    }
49
50    public override IOperation Apply(IScope scope) {
51      differential = GetVariableValue<BoolData>("Differential", scope, true).Data;
52      theilInequaliy = GetVariableValue<DoubleData>("TheilInequalityCoefficient", scope, false, false);
53      if(theilInequaliy == null) {
54        theilInequaliy = new DoubleData();
55        scope.AddVariable(new HeuristicLab.Core.Variable(scope.TranslateName("TheilInequalityCoefficient"), theilInequaliy));
56      }
57
58      return base.Apply(scope);
59    }
60
61    public override void Evaluate(int start, int end) {
62      double errorsSquaredSum = 0.0;
63      double estimatedSquaredSum = 0.0;
64      double originalSquaredSum = 0.0;
65      for(int sample = start; sample < end; sample++) {
66        double prevValue = 0.0;
67        if(differential) prevValue = GetOriginalValue(sample - 1);
68        double estimatedChange = GetEstimatedValue(sample) - prevValue;
69        double originalChange = GetOriginalValue(sample) - prevValue;
70        SetOriginalValue(sample, estimatedChange + prevValue);
71        if(!double.IsNaN(originalChange) && !double.IsInfinity(originalChange)) {
72          double error = estimatedChange - originalChange;
73          errorsSquaredSum += error * error;
74          estimatedSquaredSum += estimatedChange * estimatedChange;
75          originalSquaredSum += originalChange * originalChange;
76        }
77      }
78      int nSamples = end - start;
79      double quality = Math.Sqrt(errorsSquaredSum / nSamples) / (Math.Sqrt(estimatedSquaredSum / nSamples) + Math.Sqrt(originalSquaredSum / nSamples));
80      if(double.IsNaN(quality) || double.IsInfinity(quality))
81        quality = double.MaxValue;
82      theilInequaliy.Data = quality;
83    }
84  }
85}
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