Changeset 12843 for branches/HiveStatistics/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SymbolicClassificationPruningOperator.cs

Timestamp:

08/11/15 10:11:47 (9 years ago)

Author:

ascheibe

Message:

#2388 merged trunk into branch

Location:

branches/HiveStatistics/sources

Files:

• . (modified) (2 props)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Classification (modified) (1 prop)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SymbolicClassificationPruningOperator.cs (modified) (6 diffs)

branches/HiveStatistics/sources

@@ -23 +23 @@
 bin
 protoc.exe
+obj

@@ -23 +23 @@
 bin
 protoc.exe
+obj

branches/HiveStatistics/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SymbolicClassificationPruningOperator.cs

@@ -35 +35 @@
   public class SymbolicClassificationPruningOperator : SymbolicDataAnalysisExpressionPruningOperator {
     private const string ModelCreatorParameterName = "ModelCreator";
+    private const string EvaluatorParameterName = "Evaluator";
 
     #region parameter properties
     public ILookupParameter<ISymbolicClassificationModelCreator> ModelCreatorParameter {
       get { return (ILookupParameter<ISymbolicClassificationModelCreator>)Parameters[ModelCreatorParameterName]; }
+    }
+
+    public ILookupParameter<ISymbolicClassificationSingleObjectiveEvaluator> EvaluatorParameter {
+      get {
+        return (ILookupParameter<ISymbolicClassificationSingleObjectiveEvaluator>)Parameters[EvaluatorParameterName];
+      }
     }
     #endregion
@@ -51 +58 @@
       : base(impactValuesCalculator) {
       Parameters.Add(new LookupParameter<ISymbolicClassificationModelCreator>(ModelCreatorParameterName));
+      Parameters.Add(new LookupParameter<ISymbolicClassificationSingleObjectiveEvaluator>(EvaluatorParameterName));
+    }
+
+    [StorableHook(HookType.AfterDeserialization)]
+    private void AfterDeserialization() {
+      // BackwardsCompatibility3.3
+      #region Backwards compatible code, remove with 3.4
+      base.ImpactValuesCalculator = new SymbolicClassificationSolutionImpactValuesCalculator();
+      if (!Parameters.ContainsKey(EvaluatorParameterName)) {
+        Parameters.Add(new LookupParameter<ISymbolicClassificationSingleObjectiveEvaluator>(EvaluatorParameterName));
+      }
+      #endregion
     }
 
@@ -62 +81 @@
 
     protected override double Evaluate(IDataAnalysisModel model) {
-      var classificationModel = (IClassificationModel)model;
+      var evaluator = EvaluatorParameter.ActualValue;
+      var classificationModel = (ISymbolicClassificationModel)model;
       var classificationProblemData = (IClassificationProblemData)ProblemDataParameter.ActualValue;
       var rows = Enumerable.Range(FitnessCalculationPartitionParameter.ActualValue.Start, FitnessCalculationPartitionParameter.ActualValue.Size);
-
-      return Evaluate(classificationModel, classificationProblemData, rows);
-    }
-
-    private static double Evaluate(IClassificationModel model, IClassificationProblemData problemData, IEnumerable<int> rows) {
-      var estimatedValues = model.GetEstimatedClassValues(problemData.Dataset, rows);
-      var targetValues = problemData.Dataset.GetDoubleValues(problemData.TargetVariable, rows);
-      OnlineCalculatorError errorState;
-      var quality = OnlineAccuracyCalculator.Calculate(targetValues, estimatedValues, out errorState);
-      if (errorState != OnlineCalculatorError.None) return double.NaN;
-      return quality;
+      return evaluator.Evaluate(this.ExecutionContext, classificationModel.SymbolicExpressionTree, classificationProblemData, rows);
     }
 
@@ -86 +96 @@
 
       var nodes = clonedTree.Root.GetSubtree(0).GetSubtree(0).IterateNodesPrefix().ToList();
-      double quality = Evaluate(model, problemData, rows);
+      double qualityForImpactsCalculation = double.NaN;
 
       for (int i = 0; i < nodes.Count; ++i) {
@@ -92 +102 @@
         if (node is ConstantTreeNode) continue;
 
-        double impactValue, replacementValue;
-        impactValuesCalculator.CalculateImpactAndReplacementValues(model, node, problemData, rows, out impactValue, out replacementValue, quality);
+        double impactValue, replacementValue, newQualityForImpactsCalculation;
+        impactValuesCalculator.CalculateImpactAndReplacementValues(model, node, problemData, rows, out impactValue, out replacementValue, out newQualityForImpactsCalculation, qualityForImpactsCalculation);
 
         if (pruneOnlyZeroImpactNodes && !impactValue.IsAlmost(0.0)) continue;
@@ -104 +114 @@
         i += node.GetLength() - 1; // skip subtrees under the node that was folded
 
-        quality -= impactValue;
+        qualityForImpactsCalculation = newQualityForImpactsCalculation;
       }
       return model.SymbolicExpressionTree;

@@ -23 +23 @@
 bin
 protoc.exe
+obj