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source: branches/3044_variableScaling/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectiveTrainingBestSolutionAnalyzer.cs @ 17387

Last change on this file since 17387 was 17180, checked in by swagner, 5 years ago

#2875: Removed years in copyrights

File size: 5.7 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 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 single objective symbolic classification problems.
31  /// </summary>
32  [Item("SymbolicClassificationSingleObjectiveTrainingBestSolutionAnalyzer", "An operator that analyzes the training best symbolic classification solution for single objective symbolic classification problems.")]
33  [StorableType("1E179E22-DD6C-4914-8FAA-AB8F7F9B7F7F")]
34  public sealed class SymbolicClassificationSingleObjectiveTrainingBestSolutionAnalyzer : SymbolicDataAnalysisSingleObjectiveTrainingBestSolutionAnalyzer<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 = "UpperEstimationLimit";
40    #region parameter properties
41    public ILookupParameter<IClassificationProblemData> ProblemDataParameter {
42      get { return (ILookupParameter<IClassificationProblemData>)Parameters[ProblemDataParameterName]; }
43    }
44    public IValueLookupParameter<ISymbolicClassificationModelCreator> ModelCreatorParameter {
45      get { return (IValueLookupParameter<ISymbolicClassificationModelCreator>)Parameters[ModelCreatorParameterName]; }
46    }
47    ILookupParameter<ISymbolicClassificationModelCreator> ISymbolicClassificationModelCreatorOperator.ModelCreatorParameter {
48      get { return ModelCreatorParameter; }
49    }
50    public ILookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter> SymbolicDataAnalysisTreeInterpreterParameter {
51      get { return (ILookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter>)Parameters[SymbolicDataAnalysisTreeInterpreterParameterName]; }
52    }
53    public IValueLookupParameter<DoubleLimit> EstimationLimitsParameter {
54      get { return (IValueLookupParameter<DoubleLimit>)Parameters[EstimationLimitsParameterName]; }
55    }
56    #endregion
57
58
59    [StorableConstructor]
60    private SymbolicClassificationSingleObjectiveTrainingBestSolutionAnalyzer(StorableConstructorFlag _) : base(_) { }
61    private SymbolicClassificationSingleObjectiveTrainingBestSolutionAnalyzer(SymbolicClassificationSingleObjectiveTrainingBestSolutionAnalyzer original, Cloner cloner) : base(original, cloner) { }
62    public SymbolicClassificationSingleObjectiveTrainingBestSolutionAnalyzer()
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
70    public override IDeepCloneable Clone(Cloner cloner) {
71      return new SymbolicClassificationSingleObjectiveTrainingBestSolutionAnalyzer(this, cloner);
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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