Changeset 8531 for trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective

Timestamp:

08/28/12 13:11:15 (12 years ago)

Author:

mkommend

Message:

#1919: Refactored calculation of thresholds for SymbolicDiscriminantFunctionClassficationModels and removed the automatic recalculation of thresholds during solution creation.

Location:

trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective

Files:

• SymbolicClassificationSingleObjectiveTrainingBestSolutionAnalyzer.cs (modified) (1 diff)
• SymbolicClassificationSingleObjectiveTrainingParetoBestSolutionAnalyzer.cs (modified) (1 diff)
• SymbolicClassificationSingleObjectiveValidationBestSolutionAnalyzer.cs (modified) (1 diff)
• SymbolicClassificationSingleObjectiveValidationParetoBestSolutionAnalyzer.cs (modified) (1 diff)

trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectiveTrainingBestSolutionAnalyzer.cs

@@ -75 +75 @@
     protected override ISymbolicClassificationSolution CreateSolution(ISymbolicExpressionTree bestTree, double bestQuality) {
       var model = new SymbolicDiscriminantFunctionClassificationModel((ISymbolicExpressionTree)bestTree.Clone(), SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper);
-      if (ApplyLinearScaling.Value) {
-        SymbolicDiscriminantFunctionClassificationModel.Scale(model, ProblemDataParameter.ActualValue);
-      }
+      if (ApplyLinearScaling.Value) SymbolicDiscriminantFunctionClassificationModel.Scale(model, ProblemDataParameter.ActualValue);
+
+      SymbolicDiscriminantFunctionClassificationModel.SetAccuracyMaximizingThresholds(model, ProblemDataParameter.ActualValue);
       return new SymbolicDiscriminantFunctionClassificationSolution(model, (IClassificationProblemData)ProblemDataParameter.ActualValue.Clone());
     }

trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectiveTrainingParetoBestSolutionAnalyzer.cs

@@ -60 +60 @@
     protected override ISymbolicClassificationSolution CreateSolution(ISymbolicExpressionTree bestTree) {
       var model = new SymbolicDiscriminantFunctionClassificationModel((ISymbolicExpressionTree)bestTree.Clone(), SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper);
-      if (ApplyLinearScaling.Value)
-        SymbolicDiscriminantFunctionClassificationModel.Scale(model, ProblemDataParameter.ActualValue);
+      if (ApplyLinearScaling.Value) SymbolicDiscriminantFunctionClassificationModel.Scale(model, ProblemDataParameter.ActualValue);
+
+      SymbolicDiscriminantFunctionClassificationModel.SetAccuracyMaximizingThresholds(model, ProblemDataParameter.ActualValue);
       return new SymbolicDiscriminantFunctionClassificationSolution(model, (IClassificationProblemData)ProblemDataParameter.ActualValue.Clone());
     }

trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectiveValidationBestSolutionAnalyzer.cs

@@ -66 +66 @@
     protected override ISymbolicClassificationSolution CreateSolution(ISymbolicExpressionTree bestTree, double bestQuality) {
       var model = new SymbolicDiscriminantFunctionClassificationModel((ISymbolicExpressionTree)bestTree.Clone(), SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper);
-      if (ApplyLinearScaling.Value) {
-        SymbolicDiscriminantFunctionClassificationModel.Scale(model, ProblemDataParameter.ActualValue);
-      }
+      if (ApplyLinearScaling.Value) SymbolicDiscriminantFunctionClassificationModel.Scale(model, ProblemDataParameter.ActualValue);
+
+      SymbolicDiscriminantFunctionClassificationModel.SetAccuracyMaximizingThresholds(model, ProblemDataParameter.ActualValue);
       return new SymbolicDiscriminantFunctionClassificationSolution(model, (IClassificationProblemData)ProblemDataParameter.ActualValue.Clone());
     }

trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectiveValidationParetoBestSolutionAnalyzer.cs

@@ -60 +60 @@
     protected override ISymbolicClassificationSolution CreateSolution(ISymbolicExpressionTree bestTree) {
       var model = new SymbolicDiscriminantFunctionClassificationModel((ISymbolicExpressionTree)bestTree.Clone(), SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper);
-      if (ApplyLinearScaling.Value)
-        SymbolicDiscriminantFunctionClassificationModel.Scale(model, ProblemDataParameter.ActualValue);
+      if (ApplyLinearScaling.Value) SymbolicDiscriminantFunctionClassificationModel.Scale(model, ProblemDataParameter.ActualValue);
+
+      SymbolicDiscriminantFunctionClassificationModel.SetAccuracyMaximizingThresholds(model, ProblemDataParameter.ActualValue);
       return new SymbolicDiscriminantFunctionClassificationSolution(model, (IClassificationProblemData)ProblemDataParameter.ActualValue.Clone());
     }