Index: trunk/sources/HeuristicLab.Problems.DataAnalysis.Views/3.4/Classification/ClassificationEnsembleSolutionEstimatedClassValuesView.cs
===================================================================
--- trunk/sources/HeuristicLab.Problems.DataAnalysis.Views/3.4/Classification/ClassificationEnsembleSolutionEstimatedClassValuesView.cs	(revision 6729)
+++ trunk/sources/HeuristicLab.Problems.DataAnalysis.Views/3.4/Classification/ClassificationEnsembleSolutionEstimatedClassValuesView.cs	(revision 6740)
@@ -98,5 +98,5 @@
       int modelCount = Content.Model.Models.Count();
       string[,] values = new string[indizes.Length, 5 + classValuesCount + modelCount];
-      double[] target = Content.ProblemData.Dataset.GetVariableValues(Content.ProblemData.TargetVariable);
+      double[] target = Content.ProblemData.Dataset.GetDoubleValues(Content.ProblemData.TargetVariable).ToArray();
       List<List<double?>> estimatedValuesVector = GetEstimatedValues(SamplesComboBox.SelectedItem.ToString(), indizes,
                                                             Content.ClassificationSolutions);
Index: trunk/sources/HeuristicLab.Problems.DataAnalysis.Views/3.4/Classification/ClassificationSolutionConfusionMatrixView.cs
===================================================================
--- trunk/sources/HeuristicLab.Problems.DataAnalysis.Views/3.4/Classification/ClassificationSolutionConfusionMatrixView.cs	(revision 6729)
+++ trunk/sources/HeuristicLab.Problems.DataAnalysis.Views/3.4/Classification/ClassificationSolutionConfusionMatrixView.cs	(revision 6740)
@@ -114,5 +114,5 @@
         } else throw new InvalidOperationException();
 
-        double[] targetValues = Content.ProblemData.Dataset.GetEnumeratedVariableValues(Content.ProblemData.TargetVariable, rows).ToArray();
+        double[] targetValues = Content.ProblemData.Dataset.GetDoubleValues(Content.ProblemData.TargetVariable, rows).ToArray();
 
         Dictionary<double, int> classValueIndexMapping = new Dictionary<double, int>();
Index: trunk/sources/HeuristicLab.Problems.DataAnalysis.Views/3.4/Classification/ClassificationSolutionEstimatedClassValuesView.cs
===================================================================
--- trunk/sources/HeuristicLab.Problems.DataAnalysis.Views/3.4/Classification/ClassificationSolutionEstimatedClassValuesView.cs	(revision 6729)
+++ trunk/sources/HeuristicLab.Problems.DataAnalysis.Views/3.4/Classification/ClassificationSolutionEstimatedClassValuesView.cs	(revision 6740)
@@ -86,5 +86,5 @@
           string[,] values = new string[Content.ProblemData.Dataset.Rows, 5];
 
-          double[] target = Content.ProblemData.Dataset.GetVariableValues(Content.ProblemData.TargetVariable);
+          double[] target = Content.ProblemData.Dataset.GetDoubleValues(Content.ProblemData.TargetVariable).ToArray();
           double[] estimated = Content.EstimatedClassValues.ToArray();
           for (int row = 0; row < target.Length; row++) {
Index: trunk/sources/HeuristicLab.Problems.DataAnalysis.Views/3.4/Classification/DiscriminantFunctionClassificationRocCurvesView.cs
===================================================================
--- trunk/sources/HeuristicLab.Problems.DataAnalysis.Views/3.4/Classification/DiscriminantFunctionClassificationRocCurvesView.cs	(revision 6729)
+++ trunk/sources/HeuristicLab.Problems.DataAnalysis.Views/3.4/Classification/DiscriminantFunctionClassificationRocCurvesView.cs	(revision 6740)
@@ -107,5 +107,5 @@
 
         double[] estimatedValues = Content.GetEstimatedValues(rows).ToArray();
-        double[] targetClassValues = Content.ProblemData.Dataset.GetEnumeratedVariableValues(Content.ProblemData.TargetVariable, rows).ToArray();
+        double[] targetClassValues = Content.ProblemData.Dataset.GetDoubleValues(Content.ProblemData.TargetVariable, rows).ToArray();
         double minThreshold = estimatedValues.Min();
         double maxThreshold = estimatedValues.Max();
Index: trunk/sources/HeuristicLab.Problems.DataAnalysis.Views/3.4/Classification/DiscriminantFunctionClassificationSolutionEstimatedClassValuesView.cs
===================================================================
--- trunk/sources/HeuristicLab.Problems.DataAnalysis.Views/3.4/Classification/DiscriminantFunctionClassificationSolutionEstimatedClassValuesView.cs	(revision 6729)
+++ trunk/sources/HeuristicLab.Problems.DataAnalysis.Views/3.4/Classification/DiscriminantFunctionClassificationSolutionEstimatedClassValuesView.cs	(revision 6740)
@@ -51,5 +51,5 @@
           string[,] values = new string[Content.ProblemData.Dataset.Rows, 4];
 
-          double[] target = Content.ProblemData.Dataset.GetVariableValues(Content.ProblemData.TargetVariable);
+          double[] target = Content.ProblemData.Dataset.GetDoubleValues(Content.ProblemData.TargetVariable).ToArray();
           double[] estimatedClassValues = Content.EstimatedClassValues.ToArray();
           double[] estimatedValues = Content.EstimatedValues.ToArray();
Index: trunk/sources/HeuristicLab.Problems.DataAnalysis.Views/3.4/Classification/DiscriminantFunctionClassificationSolutionThresholdView.cs
===================================================================
--- trunk/sources/HeuristicLab.Problems.DataAnalysis.Views/3.4/Classification/DiscriminantFunctionClassificationSolutionThresholdView.cs	(revision 6729)
+++ trunk/sources/HeuristicLab.Problems.DataAnalysis.Views/3.4/Classification/DiscriminantFunctionClassificationSolutionThresholdView.cs	(revision 6740)
@@ -135,7 +135,9 @@
     private void FillSeriesWithDataPoints(Series series) {
       List<double> estimatedValues = Content.EstimatedValues.ToList();
+      var targetValues = Content.ProblemData.Dataset.GetDoubleValues(Content.ProblemData.TargetVariable).ToList();
+
       foreach (int row in Content.ProblemData.TrainingIndizes) {
         double estimatedValue = estimatedValues[row];
-        double targetValue = Content.ProblemData.Dataset[Content.ProblemData.TargetVariable, row];
+        double targetValue = targetValues[row];
         if (targetValue.IsAlmost((double)series.Tag)) {
           double jitterValue = random.NextDouble() * 2.0 - 1.0;
@@ -150,6 +152,6 @@
       foreach (int row in Content.ProblemData.TestIndizes) {
         double estimatedValue = estimatedValues[row];
-        double targetValue = Content.ProblemData.Dataset[Content.ProblemData.TargetVariable, row];
-        if (targetValue == (double)series.Tag) {
+        double targetValue = targetValues[row];
+        if (targetValue.IsAlmost((double)series.Tag)) {
           double jitterValue = random.NextDouble() * 2.0 - 1.0;
           DataPoint point = new DataPoint();
