Index: branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification-3.4.csproj
===================================================================
--- branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification-3.4.csproj	(revision 5613)
+++ branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification-3.4.csproj	(revision 5618)
@@ -113,8 +113,10 @@
     <Compile Include="MultiObjective\SymbolicClassificationMultiObjectiveMeanSquaredErrorTreeSizeEvaluator.cs" />
     <Compile Include="MultiObjective\SymbolicClassificationMultiObjectivePearsonRSquaredTreeSizeEvaluator.cs" />
+    <Compile Include="MultiObjective\SymbolicClassificationMultiObjectiveProblem.cs" />
     <Compile Include="SingleObjective\SymbolicClassificationSingleObjectiveEvaluator.cs" />
     <Compile Include="SingleObjective\SymbolicClassificationSingleObjectiveMeanSquaredErrorEvaluator.cs" />
     <Compile Include="SingleObjective\SymbolicClassificationSingleObjectivePearsonRSquaredEvaluator.cs" />
     <Compile Include="MultiObjective\SymbolicClassificationMultiObjectiveTrainingBestSolutionAnalyzer.cs" />
+    <Compile Include="SingleObjective\SymbolicClassificationSingleObjectiveProblem.cs" />
     <Compile Include="SingleObjective\SymbolicClassificationSingleObjectiveTrainingBestSolutionAnalyzer.cs" />
     <None Include="HeuristicLab.snk" />
Index: branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/MultiObjective/SymbolicClassificationMultiObjectiveMeanSquaredErrorTreeSizeEvaluator.cs
===================================================================
--- branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/MultiObjective/SymbolicClassificationMultiObjectiveMeanSquaredErrorTreeSizeEvaluator.cs	(revision 5613)
+++ branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/MultiObjective/SymbolicClassificationMultiObjectiveMeanSquaredErrorTreeSizeEvaluator.cs	(revision 5618)
@@ -27,5 +27,5 @@
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
 
-namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Classification.MultiObjective {
+namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Classification {
   [Item("Mean squared error & Tree size Evaluator", "Calculates the mean squared error and the tree size of a symbolic classification solution.")]
   [StorableClass]
Index: branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/MultiObjective/SymbolicClassificationMultiObjectivePearsonRSquaredTreeSizeEvaluator.cs
===================================================================
--- branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/MultiObjective/SymbolicClassificationMultiObjectivePearsonRSquaredTreeSizeEvaluator.cs	(revision 5613)
+++ branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/MultiObjective/SymbolicClassificationMultiObjectivePearsonRSquaredTreeSizeEvaluator.cs	(revision 5618)
@@ -6,5 +6,5 @@
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
 
-namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Classification.MultiObjective {
+namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Classification {
   [Item("Pearson R² & Tree size Evaluator", "Calculates the Pearson R² and the tree size of a symbolic classification solution.")]
   [StorableClass]
Index: branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/MultiObjective/SymbolicClassificationMultiObjectiveProblem.cs
===================================================================
--- branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/MultiObjective/SymbolicClassificationMultiObjectiveProblem.cs	(revision 5618)
+++ branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/MultiObjective/SymbolicClassificationMultiObjectiveProblem.cs	(revision 5618)
@@ -0,0 +1,56 @@
+﻿#region License Information
+/* HeuristicLab
+ * Copyright (C) 2002-2011 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ *
+ * This file is part of HeuristicLab.
+ *
+ * HeuristicLab is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * HeuristicLab is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
+ */
+#endregion
+using System.Linq;
+using HeuristicLab.Common;
+using HeuristicLab.Core;
+using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
+using HeuristicLab.Data;
+
+namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Classification {
+  [Item("Symbolic Classification Problem (multi objective)", "Represents a multi objective symbolic classfication problem.")]
+  [StorableClass]
+  [Creatable("Problems")]
+  public class SymbolicClassificationMultiObjectiveProblem : SymbolicDataAnalysisMultiObjectiveProblem<IClassificationProblemData, ISymbolicClassificationMultiObjectiveEvaluator, ISymbolicDataAnalysisSolutionCreator> {
+    private const double PunishmentFactor = 10;
+
+    [StorableConstructor]
+    protected SymbolicClassificationMultiObjectiveProblem(bool deserializing) : base(deserializing) { }
+    protected SymbolicClassificationMultiObjectiveProblem(SymbolicClassificationMultiObjectiveProblem original, Cloner cloner) : base(original, cloner) { }
+    public override IDeepCloneable Clone(Cloner cloner) { return new SymbolicClassificationMultiObjectiveProblem(this, cloner); }
+
+    public SymbolicClassificationMultiObjectiveProblem()
+      : base(new ClassificationProblemData(), new SymbolicClassificationMultiObjectiveMeanSquaredErrorTreeSizeEvaluator(), new SymbolicDataAnalysisExpressionTreeCreator()) {
+        Maximization = new BoolArray(new bool[] { false, false });
+      MaximumSymbolicExpressionTreeDepth.Value = 8;
+      MaximumSymbolicExpressionTreeLength.Value = 25;
+    }
+
+    protected override void UpdateEstimationLimits() {
+      if (ProblemData.TrainingPartitionStart.Value < ProblemData.TrainingPartitionEnd.Value) {
+        var targetValues = ProblemData.Dataset.GetVariableValues(ProblemData.TargetVariable, ProblemData.TrainingPartitionStart.Value, ProblemData.TrainingPartitionEnd.Value);
+        var mean = targetValues.Average();
+        var range = targetValues.Max() - targetValues.Min();
+        UpperEstimationLimit.Value = mean + PunishmentFactor * range;
+        LowerEstimationLimit.Value = mean - PunishmentFactor * range;
+      }
+    }
+  }
+}
Index: branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectiveMeanSquaredErrorEvaluator.cs
===================================================================
--- branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectiveMeanSquaredErrorEvaluator.cs	(revision 5613)
+++ branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectiveMeanSquaredErrorEvaluator.cs	(revision 5618)
@@ -28,5 +28,5 @@
 
 namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Classification {
-  [Item("Mean squared error evaluator", "Calculates the mean squared error of a symbolic classification solution.")]
+  [Item("Mean squared error Evaluator", "Calculates the mean squared error of a symbolic classification solution.")]
   [StorableClass]
   public class SymbolicClassificationSingleObjectiveMeanSquaredErrorEvaluator : SymbolicClassificationSingleObjectiveEvaluator {
Index: branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectiveProblem.cs
===================================================================
--- branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectiveProblem.cs	(revision 5618)
+++ branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectiveProblem.cs	(revision 5618)
@@ -0,0 +1,54 @@
+﻿#region License Information
+/* HeuristicLab
+ * Copyright (C) 2002-2011 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ *
+ * This file is part of HeuristicLab.
+ *
+ * HeuristicLab is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * HeuristicLab is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
+ */
+#endregion
+using System.Linq;
+using HeuristicLab.Common;
+using HeuristicLab.Core;
+using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
+
+namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Classification {
+  [Item("Symbolic Classification Problem (single objective)", "Represents a single objective symbolic classfication problem.")]
+  [StorableClass]
+  [Creatable("Problems")]
+  public class SymbolicClassificationSingleObjectiveProblem : SymbolicDataAnalysisSingleObjectiveProblem<IClassificationProblemData, ISymbolicClassificationSingleObjectiveEvaluator, ISymbolicDataAnalysisSolutionCreator> {
+    private const double PunishmentFactor = 10;
+
+    [StorableConstructor]
+    protected SymbolicClassificationSingleObjectiveProblem(bool deserializing) : base(deserializing) { }
+    protected SymbolicClassificationSingleObjectiveProblem(SymbolicClassificationSingleObjectiveProblem original, Cloner cloner) : base(original, cloner) { }
+    public override IDeepCloneable Clone(Cloner cloner) { return new SymbolicClassificationSingleObjectiveProblem(this, cloner); }
+
+    public SymbolicClassificationSingleObjectiveProblem()
+      : base(new ClassificationProblemData(), new SymbolicClassificationSingleObjectiveMeanSquaredErrorEvaluator(), new SymbolicDataAnalysisExpressionTreeCreator()) {
+      MaximumSymbolicExpressionTreeDepth.Value = 8;
+      MaximumSymbolicExpressionTreeLength.Value = 25;
+    }
+
+    protected override void UpdateEstimationLimits() {
+      if (ProblemData.TrainingPartitionStart.Value < ProblemData.TrainingPartitionEnd.Value) {
+        var targetValues = ProblemData.Dataset.GetVariableValues(ProblemData.TargetVariable, ProblemData.TrainingPartitionStart.Value, ProblemData.TrainingPartitionEnd.Value);
+        var mean = targetValues.Average();
+        var range = targetValues.Max() - targetValues.Min();
+        UpperEstimationLimit.Value = mean + PunishmentFactor * range;
+        LowerEstimationLimit.Value = mean - PunishmentFactor * range;
+      }
+    }
+  }
+}
