Changeset 12189 for trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SymbolicClassificationPruningOperator.cs
- Timestamp:
- 03/11/15 14:07:50 (10 years ago)
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-
- 1 edited
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trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SymbolicClassificationPruningOperator.cs
r12012 r12189 22 22 #endregion 23 23 24 using System.Collections.Generic; 24 25 using System.Linq; 25 26 using HeuristicLab.Common; 26 27 using HeuristicLab.Core; 28 using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding; 27 29 using HeuristicLab.Parameters; 28 30 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable; … … 32 34 [Item("SymbolicClassificationPruningOperator", "An operator which prunes symbolic classificaton trees.")] 33 35 public class SymbolicClassificationPruningOperator : SymbolicDataAnalysisExpressionPruningOperator { 34 private const string ImpactValuesCalculatorParameterName = "ImpactValuesCalculator";35 36 private const string ModelCreatorParameterName = "ModelCreator"; 36 37 … … 52 53 protected SymbolicClassificationPruningOperator(bool deserializing) : base(deserializing) { } 53 54 54 public SymbolicClassificationPruningOperator( ) {55 Parameters.Add(new ValueParameter<ISymbolicDataAnalysisSolutionImpactValuesCalculator>(ImpactValuesCalculatorParameterName, new SymbolicClassificationSolutionImpactValuesCalculator()));55 public SymbolicClassificationPruningOperator(ISymbolicDataAnalysisSolutionImpactValuesCalculator impactValuesCalculator) 56 : base(impactValuesCalculator) { 56 57 Parameters.Add(new LookupParameter<ISymbolicClassificationModelCreator>(ModelCreatorParameterName)); 57 58 } 58 59 59 protected override ISymbolicDataAnalysisModel CreateModel( ) {60 var model = ModelCreatorParameter.ActualValue.CreateSymbolicClassificationModel( SymbolicExpressionTree, Interpreter, EstimationLimits.Lower, EstimationLimits.Upper);61 var problemData = (IClassificationProblemData)ProblemData;62 var rows = problemData.TrainingIndices;63 model.RecalculateModelParameters( problemData, rows);60 protected override ISymbolicDataAnalysisModel CreateModel(ISymbolicExpressionTree tree, ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, IDataAnalysisProblemData problemData, DoubleLimit estimationLimits) { 61 var model = ModelCreatorParameter.ActualValue.CreateSymbolicClassificationModel(tree, interpreter, estimationLimits.Lower, estimationLimits.Upper); 62 var classificationProblemData = (IClassificationProblemData)problemData; 63 var rows = classificationProblemData.TrainingIndices; 64 model.RecalculateModelParameters(classificationProblemData, rows); 64 65 return model; 65 66 } … … 69 70 var classificationProblemData = (IClassificationProblemData)ProblemData; 70 71 var trainingIndices = Enumerable.Range(FitnessCalculationPartition.Start, FitnessCalculationPartition.Size); 71 var estimatedValues = classificationModel.GetEstimatedClassValues(ProblemData.Dataset, trainingIndices); 72 var targetValues = ProblemData.Dataset.GetDoubleValues(classificationProblemData.TargetVariable, trainingIndices); 72 73 return Evaluate(classificationModel, classificationProblemData, trainingIndices); 74 } 75 76 private static double Evaluate(IClassificationModel model, IClassificationProblemData problemData, IEnumerable<int> rows) { 77 var estimatedValues = model.GetEstimatedClassValues(problemData.Dataset, rows); 78 var targetValues = problemData.Dataset.GetDoubleValues(problemData.TargetVariable, rows); 73 79 OnlineCalculatorError errorState; 74 80 var quality = OnlineAccuracyCalculator.Calculate(targetValues, estimatedValues, out errorState); … … 76 82 return quality; 77 83 } 84 85 public static ISymbolicExpressionTree Prune(ISymbolicExpressionTree tree, ISymbolicClassificationModelCreator modelCreator, 86 SymbolicClassificationSolutionImpactValuesCalculator impactValuesCalculator, ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, 87 IClassificationProblemData problemData, DoubleLimit estimationLimits, IEnumerable<int> rows, 88 double nodeImpactThreshold = 0.0, bool pruneOnlyZeroImpactNodes = false) { 89 var clonedTree = (ISymbolicExpressionTree)tree.Clone(); 90 var model = modelCreator.CreateSymbolicClassificationModel(clonedTree, interpreter, estimationLimits.Lower, estimationLimits.Upper); 91 92 var nodes = clonedTree.IterateNodesPrefix().ToList(); 93 double quality = Evaluate(model, problemData, rows); 94 95 for (int i = 0; i < nodes.Count; ++i) { 96 var node = nodes[i]; 97 if (node is ConstantTreeNode) continue; 98 99 double impactValue, replacementValue; 100 impactValuesCalculator.CalculateImpactAndReplacementValues(model, node, problemData, rows, out impactValue, out replacementValue, quality); 101 102 if (pruneOnlyZeroImpactNodes) { 103 if (!impactValue.IsAlmost(0.0)) continue; 104 } else if (nodeImpactThreshold < impactValue) { 105 continue; 106 } 107 108 var constantNode = (ConstantTreeNode)node.Grammar.GetSymbol("Constant").CreateTreeNode(); 109 constantNode.Value = replacementValue; 110 111 ReplaceWithConstant(node, constantNode); 112 i += node.GetLength() - 1; // skip subtrees under the node that was folded 113 114 quality -= impactValue; 115 } 116 return model.SymbolicExpressionTree; 117 } 78 118 } 79 119 }
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