Changeset 2036 for trunk

Timestamp:

06/09/09 14:38:46 (15 years ago)

Author:

gkronber

Message:

Removed commented code fragments. #624

Location:

trunk/sources/HeuristicLab.SupportVectorMachines/3.2

Files:

• SupportVectorCreator.cs (modified) (2 diffs)
• SupportVectorEvaluator.cs (modified) (2 diffs)

trunk/sources/HeuristicLab.SupportVectorMachines/3.2/SupportVectorCreator.cs

@@ -53 +53 @@
       AddVariableInfo(new VariableInfo("SVMGamma", "Gamma parameter in kernel function", typeof(DoubleData), VariableKind.In));
       AddVariableInfo(new VariableInfo("SVMModel", "Represent the model learned by the SVM", typeof(SVMModel), VariableKind.New | VariableKind.Out));
-//    AddVariableInfo(new VariableInfo("SVMRangeTransform", "The applied transformation during the learning the model", typeof(SVMRangeTransform), VariableKind.New | VariableKind.Out));
     }
 
@@ -95 +94 @@
         modelData.RangeTransform = rangeTransform;
         scope.AddVariable(new Variable(scope.TranslateName("SVMModel"), modelData));
-        //SVMRangeTransform rangeTransformData = new SVMRangeTransform();
-        //rangeTransformData.Data = rangeTransform;
-        //scope.AddVariable(new Variable(scope.TranslateName("SVMRangeTransform"), rangeTransformData));
         return null;
       } else {

trunk/sources/HeuristicLab.SupportVectorMachines/3.2/SupportVectorEvaluator.cs

@@ -41 +41 @@
 
       AddVariableInfo(new VariableInfo("SVMModel", "Represent the model learned by the SVM", typeof(SVMModel), VariableKind.In));
-      // AddVariableInfo(new VariableInfo("SVMRangeTransform", "The applied transformation during the learning the model", typeof(SVMRangeTransform), VariableKind.In));
-
       AddVariableInfo(new VariableInfo("Values", "Target vs predicted values", typeof(DoubleMatrixData), VariableKind.New | VariableKind.Out));
     }
@@ -55 +53 @@
 
       SVMModel modelData = GetVariableValue<SVMModel>("SVMModel", scope, true);
-      // SVM.RangeTransform rangeTransform = GetVariableValue<SVMRangeTransform>("SVMRangeTransform", scope, true).Data;
-
       SVM.Problem problem = SVMHelper.CreateSVMProblem(dataset, allowedFeatures, targetVariable, start, end);
       SVM.Problem scaledProblem = SVM.Scaling.Scale(problem, modelData.RangeTransform);