Index: trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectiveOverfittingAnalyzer.cs
===================================================================
--- trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectiveOverfittingAnalyzer.cs	(revision 5822)
+++ trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectiveOverfittingAnalyzer.cs	(revision 5823)
@@ -85,8 +85,13 @@
                                     select EvaluatorParameter.ActualValue.Evaluate(childContext, tree, ProblemDataParameter.ActualValue, rows))
                                    .ToArray();
-      double r = alglib.spearmancorr2(trainingQuality, validationQuality);
+      double r = 0.0;
+      try {
+        r = alglib.spearmancorr2(trainingQuality, validationQuality);
+      }
+      catch (alglib.alglibexception) {
+        r = 0.0;
+      }
 
       TrainingValidationQualityCorrelationParameter.ActualValue = new DoubleValue(r);
-
       if (TrainingValidationQualityCorrelationTableParameter.ActualValue == null) {
         var dataTable = new DataTable(TrainingValidationQualityCorrelationTableParameter.Name, TrainingValidationQualityCorrelationTableParameter.Description);
Index: trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectivePearsonRSquaredEvaluator.cs
===================================================================
--- trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectivePearsonRSquaredEvaluator.cs	(revision 5822)
+++ trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectivePearsonRSquaredEvaluator.cs	(revision 5823)
@@ -59,5 +59,5 @@
       }
       catch (ArgumentException) {
-        // if R² cannot be calculated because of NaN or ininity elements => return worst possible fitness valuse
+        // if R² cannot be calculated because of NaN or ininity elements => return worst possible fitness value
         return 0.0;
       }
Index: trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveOverfittingAnalyzer.cs
===================================================================
--- trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveOverfittingAnalyzer.cs	(revision 5822)
+++ trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveOverfittingAnalyzer.cs	(revision 5823)
@@ -85,5 +85,11 @@
                                     select EvaluatorParameter.ActualValue.Evaluate(childContext, tree, ProblemDataParameter.ActualValue, rows))
                                    .ToArray();
-      double r = alglib.spearmancorr2(trainingQuality, validationQuality);
+      double r = 0.0;
+      try {
+        r = alglib.spearmancorr2(trainingQuality, validationQuality);
+      }
+      catch (alglib.alglibexception) {
+        r = 0.0;
+      }
 
       TrainingValidationQualityCorrelationParameter.ActualValue = new DoubleValue(r);
Index: trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectivePearsonRSquaredEvaluator.cs
===================================================================
--- trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectivePearsonRSquaredEvaluator.cs	(revision 5822)
+++ trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectivePearsonRSquaredEvaluator.cs	(revision 5823)
@@ -59,5 +59,5 @@
       }
       catch (ArgumentException) {
-        // if R² cannot be calculated because of NaN or ininity elements => return worst possible fitness valuse
+        // if R² cannot be calculated because of NaN or ininity elements => return worst possible fitness value
         return 0.0;
       }
Index: trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Evaluators/SymbolicDataAnalysisEvaluator.cs
===================================================================
--- trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Evaluators/SymbolicDataAnalysisEvaluator.cs	(revision 5822)
+++ trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Evaluators/SymbolicDataAnalysisEvaluator.cs	(revision 5823)
@@ -93,4 +93,6 @@
       int samplesStart = EvaluationPartitionParameter.ActualValue.Start;
       int samplesEnd = EvaluationPartitionParameter.ActualValue.End;
+      int testPartitionStart = ProblemDataParameter.ActualValue.TestPartition.Start;
+      int testPartitionEnd = ProblemDataParameter.ActualValue.TestPartition.End;
 
       if (samplesEnd < samplesStart) throw new ArgumentException("Start value is larger than end value.");
@@ -98,5 +100,5 @@
       if (count == 0) count = 1;
       return RandomEnumerable.SampleRandomNumbers(seed, samplesStart, samplesEnd, count)
-        .Where(i => i < ProblemDataParameter.ActualValue.TestPartition.Start || ProblemDataParameter.ActualValue.TestPartition.End <= i);
+        .Where(i => i < testPartitionStart || testPartitionEnd <= i);
     }
   }
