source: stable/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectiveValidationParetoBestSolutionAnalyzer.cs @ 17097

Last change on this file since 17097 was 17097, checked in by mkommend, 3 years ago

#2520: Merged 16565 - 16579 into stable.

File size: 4.3 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 collects the validation Pareto-best symbolic classification solutions for single objective symbolic classification problems.
31  /// </summary>
32  [Item("SymbolicClassificationSingleObjectiveValidationParetoBestSolutionAnalyzer", "An operator that collects the validation Pareto-best symbolic classification solutions for single objective symbolic classification problems.")]
33  [StorableType("DCD4AFE1-B6E5-4A97-BEB3-1BF3E336DD78")]
34  public sealed class SymbolicClassificationSingleObjectiveValidationParetoBestSolutionAnalyzer : SymbolicDataAnalysisSingleObjectiveValidationParetoBestSolutionAnalyzer<ISymbolicClassificationSolution, ISymbolicClassificationSingleObjectiveEvaluator, IClassificationProblemData>, ISymbolicClassificationModelCreatorOperator {
35    private const string ModelCreatorParameterName = "ModelCreator";
36    #region parameter properties
37    public IValueLookupParameter<ISymbolicClassificationModelCreator> ModelCreatorParameter {
38      get { return (IValueLookupParameter<ISymbolicClassificationModelCreator>)Parameters[ModelCreatorParameterName]; }
39    }
40    ILookupParameter<ISymbolicClassificationModelCreator> ISymbolicClassificationModelCreatorOperator.ModelCreatorParameter {
41      get { return ModelCreatorParameter; }
42    }
43    #endregion
44
45    [StorableConstructor]
46    private SymbolicClassificationSingleObjectiveValidationParetoBestSolutionAnalyzer(StorableConstructorFlag _) : base(_) { }
47    private SymbolicClassificationSingleObjectiveValidationParetoBestSolutionAnalyzer(SymbolicClassificationSingleObjectiveValidationParetoBestSolutionAnalyzer original, Cloner cloner) : base(original, cloner) { }
48    public SymbolicClassificationSingleObjectiveValidationParetoBestSolutionAnalyzer()
49      : base() {
50      Parameters.Add(new ValueLookupParameter<ISymbolicClassificationModelCreator>(ModelCreatorParameterName, ""));
51    }
52    public override IDeepCloneable Clone(Cloner cloner) {
53      return new SymbolicClassificationSingleObjectiveValidationParetoBestSolutionAnalyzer(this, cloner);
54    }
55
56    [StorableHook(HookType.AfterDeserialization)]
57    private void AfterDeserialization() {
58      // BackwardsCompatibility3.4
59      #region Backwards compatible code, remove with 3.5
60      if (!Parameters.ContainsKey(ModelCreatorParameterName))
61        Parameters.Add(new ValueLookupParameter<ISymbolicClassificationModelCreator>(ModelCreatorParameterName, ""));
62      #endregion
63    }
64
65    protected override ISymbolicClassificationSolution CreateSolution(ISymbolicExpressionTree bestTree) {
66      var model = ModelCreatorParameter.ActualValue.CreateSymbolicClassificationModel(ProblemDataParameter.ActualValue.TargetVariable, (ISymbolicExpressionTree)bestTree.Clone(), SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper);
67      if (ApplyLinearScalingParameter.ActualValue.Value) model.Scale(ProblemDataParameter.ActualValue);
68
69      model.RecalculateModelParameters(ProblemDataParameter.ActualValue, ProblemDataParameter.ActualValue.TrainingIndices);
70      return model.CreateClassificationSolution((IClassificationProblemData)ProblemDataParameter.ActualValue.Clone());
71    }
72  }
73}
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