Index: branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/MultiObjective/SymbolicClassificationMultiObjectiveProblem.cs
===================================================================
--- branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/MultiObjective/SymbolicClassificationMultiObjectiveProblem.cs	(revision 7771)
+++ branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/MultiObjective/SymbolicClassificationMultiObjectiveProblem.cs	(revision 7805)
@@ -25,4 +25,5 @@
 using HeuristicLab.Parameters;
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
+using HeuristicLab.Problems.Instances;
 
 namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Classification {
@@ -30,5 +31,6 @@
   [StorableClass]
   [Creatable("Problems")]
-  public class SymbolicClassificationMultiObjectiveProblem : SymbolicDataAnalysisMultiObjectiveProblem<IClassificationProblemData, ISymbolicClassificationMultiObjectiveEvaluator, ISymbolicDataAnalysisSolutionCreator>, IClassificationProblem {
+  public class SymbolicClassificationMultiObjectiveProblem : SymbolicDataAnalysisMultiObjectiveProblem<IClassificationProblemData, ISymbolicClassificationMultiObjectiveEvaluator, ISymbolicDataAnalysisSolutionCreator>, IClassificationProblem,
+    IProblemInstanceConsumer<IClassificationProblemData>, IProblemInstanceExporter<IClassificationProblemData> {
     private const double PunishmentFactor = 10;
     private const int InitialMaximumTreeDepth = 8;
@@ -107,4 +109,19 @@
       }
     }
+
+    #region Import & Export
+    public new void Load(IClassificationProblemData data) {
+      base.Load(data);
+    }
+
+    public IClassificationProblemData Export() {
+      if (ProblemData is IClassificationProblemData) {
+        return ProblemData;
+      } else {
+        ClassificationProblemData claData = new ClassificationProblemData(ProblemData.Dataset, ProblemData.AllowedInputVariables, ProblemData.TargetVariable);
+        return base.Export(claData);
+      }
+    }
+    #endregion
   }
 }
Index: branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectiveProblem.cs
===================================================================
--- branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectiveProblem.cs	(revision 7771)
+++ branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectiveProblem.cs	(revision 7805)
@@ -31,5 +31,5 @@
   [Creatable("Problems")]
   public class SymbolicClassificationSingleObjectiveProblem : SymbolicDataAnalysisSingleObjectiveProblem<IClassificationProblemData, ISymbolicClassificationSingleObjectiveEvaluator, ISymbolicDataAnalysisSolutionCreator>, IClassificationProblem,
-    IProblemInstanceConsumer<ClassificationProblemData>, IProblemInstanceExporter<ClassificationProblemData> {
+    IProblemInstanceConsumer<IClassificationProblemData>, IProblemInstanceExporter<IClassificationProblemData> {
     private const double PunishmentFactor = 10;
     private const int InitialMaximumTreeDepth = 8;
@@ -112,14 +112,14 @@
 
     #region Import & Export
-    public void Load(ClassificationProblemData data) {
+    public new void Load(IClassificationProblemData data) {
       base.Load(data);
     }
 
-    public ClassificationProblemData Export() {
-      if (ProblemData is ClassificationProblemData) {
-        return (ClassificationProblemData)ProblemData;
+    public IClassificationProblemData Export() {
+      if (ProblemData is IClassificationProblemData) {
+        return ProblemData;
       } else {
         ClassificationProblemData claData = new ClassificationProblemData(ProblemData.Dataset, ProblemData.AllowedInputVariables, ProblemData.TargetVariable);
-        return (ClassificationProblemData)base.Export(claData);
+        return base.Export(claData);
       }
     }
