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source: trunk/sources/HeuristicLab.GP.StructureIdentification/3.3/HL2TreeEvaluatorInjector.cs @ 2375

Last change on this file since 2375 was 2327, checked in by gkronber, 15 years ago

Applied changes in modeling plugins that are necessary for the new model analyzer (#722)

  • predictor has properties for the lower and upper limit of the predicted value
  • added views for predictors that show the limits (also added a new view for GeneticProgrammingModel that shows the size and height of the model)
  • Reintroduced TreeEvaluatorInjectors that read a PunishmentFactor and calculate the lower and upper limits for estimated values (limits are set in the tree evaluators)
  • Added operators to create Predictors. Changed modeling algorithms to use the predictors for the calculation of final model qualities and variable impacts (to be compatible with the new model analyzer the predictors use a very large PunishmentFactor)
  • replaced all private implementations of double.IsAlmost and use HL.Commons instead (see #733 r2324)
  • Implemented operator SolutionExtractor and moved BestSolutionStorer from HL.Logging to HL.Modeling (fixes #734)
File size: 3.1 KB
Line 
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.GP.Interfaces;
29using HeuristicLab.Modeling;
30using HeuristicLab.DataAnalysis;
31
32namespace HeuristicLab.GP.StructureIdentification {
33  public class HL2TreeEvaluatorInjector : OperatorBase {
34    public HL2TreeEvaluatorInjector()
35      : base() {
36      AddVariableInfo(new VariableInfo("Dataset", "The dataset", typeof(Dataset), VariableKind.In));
37      AddVariableInfo(new VariableInfo("TrainingSamplesStart", "Start index of training set", typeof(DoubleData), VariableKind.In));
38      AddVariableInfo(new VariableInfo("TrainingSamplesEnd", "End index of training set", typeof(DoubleData), VariableKind.In));
39      AddVariableInfo(new VariableInfo("TargetVariable", "Index of the target variable", typeof(IntData), VariableKind.In));
40      AddVariableInfo(new VariableInfo("PunishmentFactor", "The punishment factor limits the estimated values to a certain range", typeof(DoubleData), VariableKind.In));
41      AddVariableInfo(new VariableInfo("TreeEvaluator", "The tree evaluator to evaluate models", typeof(ITreeEvaluator), VariableKind.New));
42    }
43
44    public override string Description {
45      get { return "Injects a HL2 compatible tree evaluator."; }
46    }
47
48    public override IOperation Apply(IScope scope) {
49      double punishmentFactor = GetVariableValue<DoubleData>("PunishmentFactor", scope, true).Data;
50      Dataset dataset = GetVariableValue<Dataset>("Dataset", scope, true);
51      int start = GetVariableValue<IntData>("TrainingSamplesStart", scope, true).Data;
52      int end = GetVariableValue<IntData>("TrainingSamplesEnd", scope, true).Data;
53      int targetVariable = GetVariableValue<IntData>("TargetVariable", scope, true).Data;
54      double mean = dataset.GetMean(targetVariable, start, end);
55      double range = dataset.GetRange(targetVariable, start, end);
56      double minEstimatedValue = mean - punishmentFactor * range;
57      double maxEstimatedValue = mean + punishmentFactor * range;
58      HL2TreeEvaluator evaluator = new HL2TreeEvaluator(minEstimatedValue, maxEstimatedValue);
59      scope.AddVariable(new HeuristicLab.Core.Variable(scope.TranslateName("TreeEvaluator"), evaluator));
60      return null;
61    }
62  }
63}
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