Changeset 8972 for trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification

Timestamp:

11/29/12 10:59:55 (11 years ago)

Author:

mkommend

Message:

#1951: Changed SymbolicDataAnalysisModel.Scale to a protected instance method, added the method in the classificaton and regression models and adapted all calls to the Scale method.

Location:

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

Files:

• Interfaces/ISymbolicClassificationModel.cs (modified) (1 diff)
• MultiObjective/SymbolicClassificationMultiObjectiveTrainingBestSolutionAnalyzer.cs (modified) (1 diff)
• MultiObjective/SymbolicClassificationMultiObjectiveValidationBestSolutionAnalyzer.cs (modified) (1 diff)
• SingleObjective/SymbolicClassificationSingleObjectivePenaltyScoreEvaluator.cs (modified) (1 diff)
• SingleObjective/SymbolicClassificationSingleObjectiveTrainingBestSolutionAnalyzer.cs (modified) (1 diff)
• SingleObjective/SymbolicClassificationSingleObjectiveTrainingParetoBestSolutionAnalyzer.cs (modified) (1 diff)
• SingleObjective/SymbolicClassificationSingleObjectiveValidationBestSolutionAnalyzer.cs (modified) (1 diff)
• SingleObjective/SymbolicClassificationSingleObjectiveValidationParetoBestSolutionAnalyzer.cs (modified) (1 diff)
• SymbolicClassificationModel.cs (modified) (1 diff)

trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/Interfaces/ISymbolicClassificationModel.cs

@@ -27 +27 @@
     void RecalculateModelParameters(IClassificationProblemData problemData, IEnumerable<int> rows);
     new ISymbolicClassificationSolution CreateClassificationSolution(IClassificationProblemData problemData);
+
+    void Scale(IClassificationProblemData problemData);
   }
 }

trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/MultiObjective/SymbolicClassificationMultiObjectiveTrainingBestSolutionAnalyzer.cs

@@ -82 +82 @@
     protected override ISymbolicClassificationSolution CreateSolution(ISymbolicExpressionTree bestTree, double[] bestQuality) {
       var model = ModelCreatorParameter.ActualValue.CreateSymbolicClassificationModel((ISymbolicExpressionTree)bestTree.Clone(), SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper);
-      if (ApplyLinearScalingParameter.ActualValue.Value) SymbolicClassificationModel.Scale(model, ProblemDataParameter.ActualValue, ProblemDataParameter.ActualValue.TargetVariable);
+      if (ApplyLinearScalingParameter.ActualValue.Value) model.Scale(ProblemDataParameter.ActualValue);
 
       model.RecalculateModelParameters(ProblemDataParameter.ActualValue, ProblemDataParameter.ActualValue.TrainingIndices);

trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/MultiObjective/SymbolicClassificationMultiObjectiveValidationBestSolutionAnalyzer.cs

@@ -72 +72 @@
     protected override ISymbolicClassificationSolution CreateSolution(ISymbolicExpressionTree bestTree, double[] bestQualities) {
       var model = ModelCreatorParameter.ActualValue.CreateSymbolicClassificationModel((ISymbolicExpressionTree)bestTree.Clone(), SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper);
-      if (ApplyLinearScalingParameter.ActualValue.Value) SymbolicClassificationModel.Scale(model, ProblemDataParameter.ActualValue, ProblemDataParameter.ActualValue.TargetVariable);
+      if (ApplyLinearScalingParameter.ActualValue.Value) model.Scale(ProblemDataParameter.ActualValue);
 
       model.RecalculateModelParameters(ProblemDataParameter.ActualValue, ProblemDataParameter.ActualValue.TrainingIndices);

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

@@ -92 +92 @@
 
       var model = ModelCreatorParameter.ActualValue.CreateSymbolicClassificationModel(tree, SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper);
-      if (ApplyLinearScalingParameter.ActualValue.Value) SymbolicClassificationModel.Scale(model, problemData, problemData.TargetVariable);
+      if (ApplyLinearScalingParameter.ActualValue.Value) model.Scale(problemData);
       model.RecalculateModelParameters(problemData, rows);
       double penalty = Calculate(model, problemData, rows);

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

@@ -82 +82 @@
     protected override ISymbolicClassificationSolution CreateSolution(ISymbolicExpressionTree bestTree, double bestQuality) {
       var model = ModelCreatorParameter.ActualValue.CreateSymbolicClassificationModel((ISymbolicExpressionTree)bestTree.Clone(), SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper);
-      if (ApplyLinearScalingParameter.ActualValue.Value) SymbolicClassificationModel.Scale(model, ProblemDataParameter.ActualValue, ProblemDataParameter.ActualValue.TargetVariable);
+      if (ApplyLinearScalingParameter.ActualValue.Value) model.Scale(ProblemDataParameter.ActualValue);
 
       model.RecalculateModelParameters(ProblemDataParameter.ActualValue, ProblemDataParameter.ActualValue.TrainingIndices);

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

@@ -65 +65 @@
     protected override ISymbolicClassificationSolution CreateSolution(ISymbolicExpressionTree bestTree) {
       var model = ModelCreatorParameter.ActualValue.CreateSymbolicClassificationModel((ISymbolicExpressionTree)bestTree.Clone(), SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper);
-      if (ApplyLinearScalingParameter.ActualValue.Value) SymbolicClassificationModel.Scale(model, ProblemDataParameter.ActualValue, ProblemDataParameter.ActualValue.TargetVariable);
+      if (ApplyLinearScalingParameter.ActualValue.Value) model.Scale(ProblemDataParameter.ActualValue);
 
       model.RecalculateModelParameters(ProblemDataParameter.ActualValue, ProblemDataParameter.ActualValue.TrainingIndices);

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

@@ -72 +72 @@
     protected override ISymbolicClassificationSolution CreateSolution(ISymbolicExpressionTree bestTree, double bestQuality) {
       var model = ModelCreatorParameter.ActualValue.CreateSymbolicClassificationModel((ISymbolicExpressionTree)bestTree.Clone(), SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper);
-      if (ApplyLinearScalingParameter.ActualValue.Value) SymbolicClassificationModel.Scale(model, ProblemDataParameter.ActualValue, ProblemDataParameter.ActualValue.TargetVariable);
+      if (ApplyLinearScalingParameter.ActualValue.Value) model.Scale(ProblemDataParameter.ActualValue);
 
       model.RecalculateModelParameters(ProblemDataParameter.ActualValue, ProblemDataParameter.ActualValue.TrainingIndices);

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

@@ -65 +65 @@
     protected override ISymbolicClassificationSolution CreateSolution(ISymbolicExpressionTree bestTree) {
       var model = ModelCreatorParameter.ActualValue.CreateSymbolicClassificationModel((ISymbolicExpressionTree)bestTree.Clone(), SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper);
-      if (ApplyLinearScalingParameter.ActualValue.Value) SymbolicClassificationModel.Scale(model, ProblemDataParameter.ActualValue, ProblemDataParameter.ActualValue.TargetVariable);
+      if (ApplyLinearScalingParameter.ActualValue.Value) model.Scale(ProblemDataParameter.ActualValue);
 
       model.RecalculateModelParameters(ProblemDataParameter.ActualValue, ProblemDataParameter.ActualValue.TrainingIndices);

trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SymbolicClassificationModel.cs

@@ -62 +62 @@
       return CreateClassificationSolution(problemData);
     }
+
+    public void Scale(IClassificationProblemData problemData) {
+      Scale(problemData, problemData.TargetVariable);
+    }
   }
 }