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source: trunk/sources/HeuristicLab.GP.StructureIdentification/3.3/Evaluators/VariableQualityImpactCalculator.cs @ 2115

Last change on this file since 2115 was 2043, checked in by gkronber, 16 years ago

Added variable impact calculation operators for support vector machines. #644 (Variable impact of CEDMA models should be calculated and stored in the result DB)

File size: 2.7 KB
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[2041]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.Text;
25using System.Xml;
26using HeuristicLab.Core;
27using HeuristicLab.Data;
28using HeuristicLab.DataAnalysis;
29using System.Linq;
30
31namespace HeuristicLab.GP.StructureIdentification {
32  public class VariableQualityImpactCalculator : HeuristicLab.Modeling.VariableQualityImpactCalculator {
33
34    public VariableQualityImpactCalculator()
35      : base() {
36      AddVariableInfo(new VariableInfo("TreeEvaluator", "The evaluator that should be used to evaluate the expression tree", typeof(ITreeEvaluator), VariableKind.In));
37      AddVariableInfo(new VariableInfo("FunctionTree", "The function tree that should be evaluated", typeof(IFunctionTree), VariableKind.In));
38      AddVariableInfo(new VariableInfo("TreeSize", "Size (number of nodes) of the tree to evaluate", typeof(IntData), VariableKind.In));
39      AddVariableInfo(new VariableInfo("PunishmentFactor", "Punishment factor for invalid estimations", typeof(DoubleData), VariableKind.In));
40    }
41
[2043]42    protected override double CalculateQuality(IScope scope, Dataset dataset, int targetVariable, ItemList<IntData> allowedFeatures, int start, int end) {
[2041]43      ITreeEvaluator evaluator = GetVariableValue<ITreeEvaluator>("TreeEvaluator", scope, true);
44      IFunctionTree tree = GetVariableValue<IFunctionTree>("FunctionTree", scope, true);
45      double punishmentFactor = GetVariableValue<DoubleData>("PunishmentFactor", scope, true).Data;
46      evaluator.PrepareForEvaluation(dataset, targetVariable, start, end, punishmentFactor, tree);
47
48      double[,] result = new double[end - start,2];
49      for (int i = start; i < end; i++) {
50        result[i - start, 0] = dataset.GetValue(i, targetVariable);
51        result[i - start,1] = evaluator.Evaluate(i);
52      }
53
54      return HeuristicLab.Modeling.SimpleMSEEvaluator.Calculate(result);
55    }
56  }
57}
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