Changeset 5736 for branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectiveTrainingBestSolutionAnalyzer.cs

Timestamp:

03/17/11 15:14:45 (13 years ago)

Author:

gkronber

Message:

#1418 implemented linear scaling for classification solutions, fixed bugs interactive simplifier view for classification solutions.

File:

• branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectiveTrainingBestSolutionAnalyzer.cs (modified) (1 diff)

branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectiveTrainingBestSolutionAnalyzer.cs

@@ -96 +96 @@
 
     protected override ISymbolicClassificationSolution CreateSolution(ISymbolicExpressionTree bestTree, double bestQuality) {
-      double[] classValues;
-      double[] thresholds;
-      var estimatedValues = SymbolicDataAnalysisTreeInterpreter.GetSymbolicExpressionTreeValues(bestTree, ProblemData.Dataset, ProblemData.TrainingIndizes)
-        .LimitToRange(LowerEstimationLimit.Value, UpperEstimationLimit.Value);
-      var targetValues = ProblemData.Dataset.GetEnumeratedVariableValues(ProblemData.TargetVariable, ProblemData.TrainingIndizes);
-      AccuracyMaximizationThresholdCalculator.CalculateThresholds(ProblemData, estimatedValues, targetValues, out classValues, out thresholds);
-      var model = new SymbolicDiscriminantFunctionClassificationModel(bestTree, SymbolicDataAnalysisTreeInterpreter, classValues, thresholds, LowerEstimationLimit.Value, UpperEstimationLimit.Value);
-      return new SymbolicDiscriminantFunctionClassificationSolution(model, ProblemData);
+      var model = new SymbolicDiscriminantFunctionClassificationModel(bestTree, SymbolicDataAnalysisTreeInterpreter, LowerEstimationLimit.Value, UpperEstimationLimit.Value);
+      var solution = new SymbolicDiscriminantFunctionClassificationSolution(model, ProblemData);
+      if (ApplyLinearScaling.Value) {
+        solution.ScaleModel();
+      }
+      return solution;
     }
   }