source: stable/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SymbolicClassificationPruningOperator.cs @ 12745

Last change on this file since 12745 was 12745, checked in by gkronber, 7 years ago

#2359, #2398: merged r12189,r12358,r12359,r12361,r12461,r12674,r12720,r12744 from trunk to stable

File size: 6.3 KB
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1#region License Information
2
3/* HeuristicLab
4 * Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
5 *
6 * This file is part of HeuristicLab.
7 *
8 * HeuristicLab is free software: you can redistribute it and/or modify
9 * it under the terms of the GNU General Public License as published by
10 * the Free Software Foundation, either version 3 of the License, or
11 * (at your option) any later version.
12 *
13 * HeuristicLab is distributed in the hope that it will be useful,
14 * but WITHOUT ANY WARRANTY; without even the implied warranty of
15 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
16 * GNU General Public License for more details.
17 *
18 * You should have received a copy of the GNU General Public License
19 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
20 */
21
22#endregion
23
24using System.Collections.Generic;
25using System.Linq;
26using HeuristicLab.Common;
27using HeuristicLab.Core;
28using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
29using HeuristicLab.Parameters;
30using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
31
32namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Classification {
33  [StorableClass]
34  [Item("SymbolicClassificationPruningOperator", "An operator which prunes symbolic classificaton trees.")]
35  public class SymbolicClassificationPruningOperator : SymbolicDataAnalysisExpressionPruningOperator {
36    private const string ModelCreatorParameterName = "ModelCreator";
37    private const string EvaluatorParameterName = "Evaluator";
38
39    #region parameter properties
40    public ILookupParameter<ISymbolicClassificationModelCreator> ModelCreatorParameter {
41      get { return (ILookupParameter<ISymbolicClassificationModelCreator>)Parameters[ModelCreatorParameterName]; }
42    }
43
44    public ILookupParameter<ISymbolicClassificationSingleObjectiveEvaluator> EvaluatorParameter {
45      get {
46        return (ILookupParameter<ISymbolicClassificationSingleObjectiveEvaluator>)Parameters[EvaluatorParameterName];
47      }
48    }
49    #endregion
50
51    protected SymbolicClassificationPruningOperator(SymbolicClassificationPruningOperator original, Cloner cloner) : base(original, cloner) { }
52    public override IDeepCloneable Clone(Cloner cloner) { return new SymbolicClassificationPruningOperator(this, cloner); }
53
54    [StorableConstructor]
55    protected SymbolicClassificationPruningOperator(bool deserializing) : base(deserializing) { }
56
57    public SymbolicClassificationPruningOperator(ISymbolicDataAnalysisSolutionImpactValuesCalculator impactValuesCalculator)
58      : base(impactValuesCalculator) {
59      Parameters.Add(new LookupParameter<ISymbolicClassificationModelCreator>(ModelCreatorParameterName));
60      Parameters.Add(new LookupParameter<ISymbolicClassificationSingleObjectiveEvaluator>(EvaluatorParameterName));
61    }
62
63    [StorableHook(HookType.AfterDeserialization)]
64    private void AfterDeserialization() {
65      // BackwardsCompatibility3.3
66      #region Backwards compatible code, remove with 3.4
67      base.ImpactValuesCalculator = new SymbolicClassificationSolutionImpactValuesCalculator();
68      if (!Parameters.ContainsKey(EvaluatorParameterName)) {
69        Parameters.Add(new LookupParameter<ISymbolicClassificationSingleObjectiveEvaluator>(EvaluatorParameterName));
70      }
71      #endregion
72    }
73
74    protected override ISymbolicDataAnalysisModel CreateModel(ISymbolicExpressionTree tree, ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, IDataAnalysisProblemData problemData, DoubleLimit estimationLimits) {
75      var model = ModelCreatorParameter.ActualValue.CreateSymbolicClassificationModel(tree, interpreter, estimationLimits.Lower, estimationLimits.Upper);
76      var classificationProblemData = (IClassificationProblemData)problemData;
77      var rows = classificationProblemData.TrainingIndices;
78      model.RecalculateModelParameters(classificationProblemData, rows);
79      return model;
80    }
81
82    protected override double Evaluate(IDataAnalysisModel model) {
83      var evaluator = EvaluatorParameter.ActualValue;
84      var classificationModel = (ISymbolicClassificationModel)model;
85      var classificationProblemData = (IClassificationProblemData)ProblemDataParameter.ActualValue;
86      var rows = Enumerable.Range(FitnessCalculationPartitionParameter.ActualValue.Start, FitnessCalculationPartitionParameter.ActualValue.Size);
87      return evaluator.Evaluate(this.ExecutionContext, classificationModel.SymbolicExpressionTree, classificationProblemData, rows);
88    }
89
90    public static ISymbolicExpressionTree Prune(ISymbolicExpressionTree tree, ISymbolicClassificationModelCreator modelCreator,
91      SymbolicClassificationSolutionImpactValuesCalculator impactValuesCalculator, ISymbolicDataAnalysisExpressionTreeInterpreter interpreter,
92      IClassificationProblemData problemData, DoubleLimit estimationLimits, IEnumerable<int> rows,
93      double nodeImpactThreshold = 0.0, bool pruneOnlyZeroImpactNodes = false) {
94      var clonedTree = (ISymbolicExpressionTree)tree.Clone();
95      var model = modelCreator.CreateSymbolicClassificationModel(clonedTree, interpreter, estimationLimits.Lower, estimationLimits.Upper);
96
97      var nodes = clonedTree.Root.GetSubtree(0).GetSubtree(0).IterateNodesPrefix().ToList();
98      double qualityForImpactsCalculation = double.NaN;
99
100      for (int i = 0; i < nodes.Count; ++i) {
101        var node = nodes[i];
102        if (node is ConstantTreeNode) continue;
103
104        double impactValue, replacementValue, newQualityForImpactsCalculation;
105        impactValuesCalculator.CalculateImpactAndReplacementValues(model, node, problemData, rows, out impactValue, out replacementValue, out newQualityForImpactsCalculation, qualityForImpactsCalculation);
106
107        if (pruneOnlyZeroImpactNodes && !impactValue.IsAlmost(0.0)) continue;
108        if (!pruneOnlyZeroImpactNodes && impactValue > nodeImpactThreshold) continue;
109
110        var constantNode = (ConstantTreeNode)node.Grammar.GetSymbol("Constant").CreateTreeNode();
111        constantNode.Value = replacementValue;
112
113        ReplaceWithConstant(node, constantNode);
114        i += node.GetLength() - 1; // skip subtrees under the node that was folded
115
116        qualityForImpactsCalculation = newQualityForImpactsCalculation;
117      }
118      return model.SymbolicExpressionTree;
119    }
120  }
121}
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