Index: trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/Linear/LinearDiscriminantAnalysis.cs
===================================================================
--- trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/Linear/LinearDiscriminantAnalysis.cs	(revision 6002)
+++ trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/Linear/LinearDiscriminantAnalysis.cs	(revision 6182)
@@ -68,7 +68,5 @@
       string targetVariable = problemData.TargetVariable;
       IEnumerable<string> allowedInputVariables = problemData.AllowedInputVariables;
-      int samplesStart = problemData.TrainingPartition.Start;
-      int samplesEnd = problemData.TrainingPartition.End;
-      IEnumerable<int> rows = Enumerable.Range(samplesStart, samplesEnd - samplesStart);
+      IEnumerable<int> rows = problemData.TrainingIndizes;
       int nClasses = problemData.ClassNames.Count();
       double[,] inputMatrix = AlglibUtil.PrepareInputMatrix(dataset, allowedInputVariables.Concat(new string[] { targetVariable }), rows);
Index: trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/Linear/LinearRegression.cs
===================================================================
--- trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/Linear/LinearRegression.cs	(revision 6002)
+++ trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/Linear/LinearRegression.cs	(revision 6182)
@@ -72,7 +72,5 @@
       string targetVariable = problemData.TargetVariable;
       IEnumerable<string> allowedInputVariables = problemData.AllowedInputVariables;
-      int samplesStart = problemData.TrainingPartition.Start;
-      int samplesEnd = problemData.TrainingPartition.End;
-      IEnumerable<int> rows = Enumerable.Range(samplesStart, samplesEnd - samplesStart);
+      IEnumerable<int> rows = problemData.TrainingIndizes;
       double[,] inputMatrix = AlglibUtil.PrepareInputMatrix(dataset, allowedInputVariables.Concat(new string[] { targetVariable }), rows);
       if (inputMatrix.Cast<double>().Any(x => double.IsNaN(x) || double.IsInfinity(x)))
Index: trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/SupportVectorMachine/SupportVectorClassification.cs
===================================================================
--- trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/SupportVectorMachine/SupportVectorClassification.cs	(revision 6002)
+++ trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/SupportVectorMachine/SupportVectorClassification.cs	(revision 6182)
@@ -122,7 +122,5 @@
       Dataset dataset = problemData.Dataset;
       string targetVariable = problemData.TargetVariable;
-      int start = problemData.TrainingPartition.Start;
-      int end = problemData.TrainingPartition.End;
-      IEnumerable<int> rows = Enumerable.Range(start, end - start);
+      IEnumerable<int> rows = problemData.TrainingIndizes;
 
       //extract SVM parameters from scope and set them
Index: trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/SupportVectorMachine/SupportVectorRegression.cs
===================================================================
--- trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/SupportVectorMachine/SupportVectorRegression.cs	(revision 6002)
+++ trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/SupportVectorMachine/SupportVectorRegression.cs	(revision 6182)
@@ -130,7 +130,5 @@
       Dataset dataset = problemData.Dataset;
       string targetVariable = problemData.TargetVariable;
-      int start = problemData.TrainingPartition.Start;
-      int end = problemData.TrainingPartition.End;
-      IEnumerable<int> rows = Enumerable.Range(start, end - start);
+      IEnumerable<int> rows = problemData.TrainingIndizes;
 
       //extract SVM parameters from scope and set them
Index: trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/kMeans/KMeansClustering.cs
===================================================================
--- trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/kMeans/KMeansClustering.cs	(revision 6002)
+++ trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/kMeans/KMeansClustering.cs	(revision 6182)
@@ -85,7 +85,5 @@
       Dataset dataset = problemData.Dataset;
       IEnumerable<string> allowedInputVariables = problemData.AllowedInputVariables;
-      int start = problemData.TrainingPartition.Start;
-      int end = problemData.TrainingPartition.End;
-      IEnumerable<int> rows = Enumerable.Range(start, end - start);
+      IEnumerable<int> rows = problemData.TrainingIndizes;
       int info;
       double[,] centers;
