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source: branches/Persistence Test/HeuristicLab.GP.StructureIdentification/3.3/HL3TreeEvaluatorInjector.cs @ 2594

Last change on this file since 2594 was 2440, checked in by gkronber, 15 years ago

Fixed #784 (ProblemInjector should be changed to read variable names instead of indexes for input and target variables)

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 HL3TreeEvaluatorInjector : OperatorBase {
34    public HL3TreeEvaluatorInjector()
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", "Name of the target variable", typeof(StringData), 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 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      string targetVariable = GetVariableValue<StringData>("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      HL3TreeEvaluator evaluator = new HL3TreeEvaluator(minEstimatedValue, maxEstimatedValue);
59      scope.AddVariable(new HeuristicLab.Core.Variable(scope.TranslateName("TreeEvaluator"), evaluator));
60      return null;
61    }
62  }
63}
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