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source: branches/2990_VariableImpactBasedFeatureSelection/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/MultiObjective/SymbolicClassificationMultiObjectiveTrainingBestSolutionAnalyzer.cs @ 16953

Last change on this file since 16953 was 16565, checked in by gkronber, 6 years ago

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

File size: 5.7 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 training best symbolic classification solution for multi objective symbolic classification problems.
31  /// </summary>
32  [Item("SymbolicClassificationMultiObjectiveTrainingBestSolutionAnalyzer", "An operator that analyzes the training best symbolic classification solution for multi objective symbolic classification problems.")]
33  [StorableType("EC30DC99-A5A8-43B0-81C1-BA9016A0A74C")]
34  public sealed class SymbolicClassificationMultiObjectiveTrainingBestSolutionAnalyzer : SymbolicDataAnalysisMultiObjectiveTrainingBestSolutionAnalyzer<ISymbolicClassificationSolution>,
35    ISymbolicDataAnalysisInterpreterOperator, ISymbolicDataAnalysisBoundedOperator, ISymbolicClassificationModelCreatorOperator {
36    private const string ProblemDataParameterName = "ProblemData";
37    private const string ModelCreatorParameterName = "ModelCreator";
38    private const string SymbolicDataAnalysisTreeInterpreterParameterName = "SymbolicDataAnalysisTreeInterpreter";
39    private const string EstimationLimitsParameterName = "EstimationLimits";
40
41    #region parameter properties
42    public ILookupParameter<IClassificationProblemData> ProblemDataParameter {
43      get { return (ILookupParameter<IClassificationProblemData>)Parameters[ProblemDataParameterName]; }
44    }
45    public IValueLookupParameter<ISymbolicClassificationModelCreator> ModelCreatorParameter {
46      get { return (IValueLookupParameter<ISymbolicClassificationModelCreator>)Parameters[ModelCreatorParameterName]; }
47    }
48    ILookupParameter<ISymbolicClassificationModelCreator> ISymbolicClassificationModelCreatorOperator.ModelCreatorParameter {
49      get { return ModelCreatorParameter; }
50    }
51    public ILookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter> SymbolicDataAnalysisTreeInterpreterParameter {
52      get { return (ILookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter>)Parameters[SymbolicDataAnalysisTreeInterpreterParameterName]; }
53    }
54    public IValueLookupParameter<DoubleLimit> EstimationLimitsParameter {
55      get { return (IValueLookupParameter<DoubleLimit>)Parameters[EstimationLimitsParameterName]; }
56    }
57    #endregion
58
59    [StorableConstructor]
60    private SymbolicClassificationMultiObjectiveTrainingBestSolutionAnalyzer(StorableConstructorFlag _) : base(_) { }
61    private SymbolicClassificationMultiObjectiveTrainingBestSolutionAnalyzer(SymbolicClassificationMultiObjectiveTrainingBestSolutionAnalyzer original, Cloner cloner) : base(original, cloner) { }
62    public SymbolicClassificationMultiObjectiveTrainingBestSolutionAnalyzer()
63      : base() {
64      Parameters.Add(new LookupParameter<IClassificationProblemData>(ProblemDataParameterName, "The problem data for the symbolic classification solution."));
65      Parameters.Add(new ValueLookupParameter<ISymbolicClassificationModelCreator>(ModelCreatorParameterName, ""));
66      Parameters.Add(new LookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter>(SymbolicDataAnalysisTreeInterpreterParameterName, "The symbolic data analysis tree interpreter for the symbolic expression tree."));
67      Parameters.Add(new ValueLookupParameter<DoubleLimit>(EstimationLimitsParameterName, "The lower and upper limit for the estimated values produced by the symbolic classification model."));
68    }
69    public override IDeepCloneable Clone(Cloner cloner) {
70      return new SymbolicClassificationMultiObjectiveTrainingBestSolutionAnalyzer(this, cloner);
71    }
72
73    [StorableHook(HookType.AfterDeserialization)]
74    private void AfterDeserialization() {
75      // BackwardsCompatibility3.4
76      #region Backwards compatible code, remove with 3.5
77      if (!Parameters.ContainsKey(ModelCreatorParameterName))
78        Parameters.Add(new ValueLookupParameter<ISymbolicClassificationModelCreator>(ModelCreatorParameterName, ""));
79      #endregion
80    }
81
82    protected override ISymbolicClassificationSolution CreateSolution(ISymbolicExpressionTree bestTree, double[] bestQuality) {
83      var model = ModelCreatorParameter.ActualValue.CreateSymbolicClassificationModel(ProblemDataParameter.ActualValue.TargetVariable, (ISymbolicExpressionTree)bestTree.Clone(), SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper);
84      if (ApplyLinearScalingParameter.ActualValue.Value) model.Scale(ProblemDataParameter.ActualValue);
85
86      model.RecalculateModelParameters(ProblemDataParameter.ActualValue, ProblemDataParameter.ActualValue.TrainingIndices);
87      return model.CreateClassificationSolution((IClassificationProblemData)ProblemDataParameter.ActualValue.Clone());
88    }
89  }
90}
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