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source: stable/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/MultiObjective/SymbolicClassificationMultiObjectiveValidationBestSolutionAnalyzer.cs @ 15231

Last change on this file since 15231 was 14186, checked in by swagner, 8 years ago

#2526: Updated year of copyrights in license headers

File size: 4.7 KB
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[5685]1#region License Information
2/* HeuristicLab
[14186]3 * Copyright (C) 2002-2016 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
[5685]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 HeuristicLab.Common;
23using HeuristicLab.Core;
24using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
25using HeuristicLab.Parameters;
26using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
27
28namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Classification {
29  /// <summary>
30  /// An operator that analyzes the validation best symbolic classification solution for multi objective symbolic classification problems.
31  /// </summary>
32  [Item("SymbolicClassificationMultiObjectiveValidationBestSolutionAnalyzer", "An operator that analyzes the validation best symbolic classification solution for multi objective symbolic classification problems.")]
33  [StorableClass]
[5720]34  public sealed class SymbolicClassificationMultiObjectiveValidationBestSolutionAnalyzer : SymbolicDataAnalysisMultiObjectiveValidationBestSolutionAnalyzer<ISymbolicClassificationSolution, ISymbolicClassificationMultiObjectiveEvaluator, IClassificationProblemData>,
[8594]35  ISymbolicDataAnalysisBoundedOperator, ISymbolicClassificationModelCreatorOperator {
36    private const string ModelCreatorParameterName = "ModelCreator";
[5770]37    private const string EstimationLimitsParameterName = "EstimationLimits";
[5720]38
39    #region parameter properties
[5770]40    public IValueLookupParameter<DoubleLimit> EstimationLimitsParameter {
41      get { return (IValueLookupParameter<DoubleLimit>)Parameters[EstimationLimitsParameterName]; }
[5720]42    }
[8594]43    public IValueLookupParameter<ISymbolicClassificationModelCreator> ModelCreatorParameter {
44      get { return (IValueLookupParameter<ISymbolicClassificationModelCreator>)Parameters[ModelCreatorParameterName]; }
45    }
46    ILookupParameter<ISymbolicClassificationModelCreator> ISymbolicClassificationModelCreatorOperator.ModelCreatorParameter {
47      get { return ModelCreatorParameter; }
48    }
[5720]49    #endregion
50
[5685]51    [StorableConstructor]
52    private SymbolicClassificationMultiObjectiveValidationBestSolutionAnalyzer(bool deserializing) : base(deserializing) { }
53    private SymbolicClassificationMultiObjectiveValidationBestSolutionAnalyzer(SymbolicClassificationMultiObjectiveValidationBestSolutionAnalyzer original, Cloner cloner) : base(original, cloner) { }
54    public SymbolicClassificationMultiObjectiveValidationBestSolutionAnalyzer()
55      : base() {
[5770]56      Parameters.Add(new ValueLookupParameter<DoubleLimit>(EstimationLimitsParameterName, "The loewr and upper limit for the estimated values produced by the symbolic classification model."));
[8594]57      Parameters.Add(new ValueLookupParameter<ISymbolicClassificationModelCreator>(ModelCreatorParameterName, ""));
[5685]58    }
59    public override IDeepCloneable Clone(Cloner cloner) {
60      return new SymbolicClassificationMultiObjectiveValidationBestSolutionAnalyzer(this, cloner);
61    }
62
[8883]63    [StorableHook(HookType.AfterDeserialization)]
64    private void AfterDeserialization() {
65      // BackwardsCompatibility3.4
66      #region Backwards compatible code, remove with 3.5
67      if (!Parameters.ContainsKey(ModelCreatorParameterName))
68        Parameters.Add(new ValueLookupParameter<ISymbolicClassificationModelCreator>(ModelCreatorParameterName, ""));
69      #endregion
70    }
[8594]71
[5685]72    protected override ISymbolicClassificationSolution CreateSolution(ISymbolicExpressionTree bestTree, double[] bestQualities) {
[14027]73      var model = ModelCreatorParameter.ActualValue.CreateSymbolicClassificationModel(ProblemDataParameter.ActualValue.TargetVariable, (ISymbolicExpressionTree)bestTree.Clone(), SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper);
[8972]74      if (ApplyLinearScalingParameter.ActualValue.Value) model.Scale(ProblemDataParameter.ActualValue);
[8531]75
[8594]76      model.RecalculateModelParameters(ProblemDataParameter.ActualValue, ProblemDataParameter.ActualValue.TrainingIndices);
77      return model.CreateClassificationSolution((IClassificationProblemData)ProblemDataParameter.ActualValue.Clone());
[5685]78    }
79  }
80}
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