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source: branches/2994-AutoDiffForIntervals/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectiveValidationBestSolutionAnalyzer.cs @ 17116

Last change on this file since 17116 was 16565, checked in by gkronber, 6 years ago

#2520: merged changes from PersistenceOverhaul branch (r16451:16564) into trunk

File size: 4.7 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2019 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 HeuristicLab.Common;
23using HeuristicLab.Core;
24using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
25using HeuristicLab.Parameters;
26using HEAL.Attic;
27
28namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Classification {
29  /// <summary>
30  /// An operator that analyzes the validation best symbolic classification solution for single objective symbolic classification problems.
31  /// </summary>
32  [Item("SymbolicClassificationSingleObjectiveValidationBestSolutionAnalyzer", "An operator that analyzes the validation best symbolic classification solution for single objective symbolic classification problems.")]
33  [StorableType("4BEB7C5A-0B3A-4276-95C6-689F8BA8E0E6")]
34  public sealed class SymbolicClassificationSingleObjectiveValidationBestSolutionAnalyzer : SymbolicDataAnalysisSingleObjectiveValidationBestSolutionAnalyzer<ISymbolicClassificationSolution, ISymbolicClassificationSingleObjectiveEvaluator, IClassificationProblemData>,
35  ISymbolicDataAnalysisBoundedOperator, ISymbolicClassificationModelCreatorOperator {
36    private const string EstimationLimitsParameterName = "EstimationLimits";
37    private const string ModelCreatorParameterName = "ModelCreator";
38
39    #region parameter properties
40    public IValueLookupParameter<DoubleLimit> EstimationLimitsParameter {
41      get { return (IValueLookupParameter<DoubleLimit>)Parameters[EstimationLimitsParameterName]; }
42    }
43    public IValueLookupParameter<ISymbolicClassificationModelCreator> ModelCreatorParameter {
44      get { return (IValueLookupParameter<ISymbolicClassificationModelCreator>)Parameters[ModelCreatorParameterName]; }
45    }
46    ILookupParameter<ISymbolicClassificationModelCreator> ISymbolicClassificationModelCreatorOperator.ModelCreatorParameter {
47      get { return ModelCreatorParameter; }
48    }
49    #endregion
50
51    [StorableConstructor]
52    private SymbolicClassificationSingleObjectiveValidationBestSolutionAnalyzer(StorableConstructorFlag _) : base(_) { }
53    private SymbolicClassificationSingleObjectiveValidationBestSolutionAnalyzer(SymbolicClassificationSingleObjectiveValidationBestSolutionAnalyzer original, Cloner cloner) : base(original, cloner) { }
54    public SymbolicClassificationSingleObjectiveValidationBestSolutionAnalyzer()
55      : base() {
56      Parameters.Add(new ValueLookupParameter<DoubleLimit>(EstimationLimitsParameterName, "The lower and upper limit for the estimated values produced by the symbolic classification model."));
57      Parameters.Add(new ValueLookupParameter<ISymbolicClassificationModelCreator>(ModelCreatorParameterName, ""));
58    }
59    public override IDeepCloneable Clone(Cloner cloner) {
60      return new SymbolicClassificationSingleObjectiveValidationBestSolutionAnalyzer(this, cloner);
61    }
62
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    }
71
72    protected override ISymbolicClassificationSolution CreateSolution(ISymbolicExpressionTree bestTree, double bestQuality) {
73      var model = ModelCreatorParameter.ActualValue.CreateSymbolicClassificationModel(ProblemDataParameter.ActualValue.TargetVariable, (ISymbolicExpressionTree)bestTree.Clone(), SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper);
74      if (ApplyLinearScalingParameter.ActualValue.Value) model.Scale(ProblemDataParameter.ActualValue);
75
76      model.RecalculateModelParameters(ProblemDataParameter.ActualValue, ProblemDataParameter.ActualValue.TrainingIndices);
77      return model.CreateClassificationSolution((IClassificationProblemData)ProblemDataParameter.ActualValue.Clone());
78    }
79  }
80}
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