Index: branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression-3.4.csproj
===================================================================
--- branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression-3.4.csproj	(revision 5601)
+++ branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression-3.4.csproj	(revision 5607)
@@ -116,4 +116,5 @@
     <Compile Include="Interfaces\ISymbolicRegressionSingleObjectiveEvaluator.cs" />
     <Compile Include="MultiObjective\SymbolicRegressionMultiObjectiveTrainingBestSolutionAnalyzer.cs" />
+    <Compile Include="SingleObjective\SymbolicRegressionSingleObjectiveValidationBestSolutionAnalyzer.cs" />
     <Compile Include="SingleObjective\SymbolicRegressionSingleObjectiveTrainingBestSolutionAnalyzer.cs" />
     <Compile Include="MultiObjective\SymbolicRegressionMultiObjectiveEvaluator.cs" />
@@ -123,4 +124,5 @@
     <Compile Include="SingleObjective\SymbolicRegressionSingleObjectiveMeanSquaredErrorEvaluator.cs" />
     <Compile Include="SingleObjective\SymbolicRegressionSingleObjectivePearsonRSquaredEvaluator.cs" />
+    <Compile Include="SymbolicRegressionSolution.cs" />
     <None Include="HeuristicLab.snk" />
     <None Include="HeuristicLabProblemsDataAnalysisSymbolicRegressionPlugin.cs.frame" />
Index: branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveMeanSquaredErrorEvaluator.cs
===================================================================
--- branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveMeanSquaredErrorEvaluator.cs	(revision 5601)
+++ branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveMeanSquaredErrorEvaluator.cs	(revision 5607)
@@ -46,6 +46,6 @@
     public override IOperation Apply() {
       IEnumerable<int> rows = GenerateRowsToEvaluate();
-      double quality = Calculate(SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, SymbolicExpressionTreeParameter.ActualValue, LowerEstimationLimit.Value, UpperEstimationLimit.Value, ProblemData, rows);
-      QualityParameter.ActualValue = new DoubleValue(quality);
+      double quality = Calculate(SymbolicDataAnalysisTreeInterpreter, SymbolicExpressionTree, LowerEstimationLimit.Value, UpperEstimationLimit.Value, ProblemData, rows);
+      Quality = new DoubleValue(quality);
       return base.Apply();
     }
@@ -57,4 +57,8 @@
       return OnlineMeanSquaredErrorEvaluator.Calculate(originalValues, boundedEstimationValues);
     }
+
+    public override double Evaluate(IExecutionContext context, ISymbolicExpressionTree tree,  IRegressionProblemData problemData, IEnumerable<int> rows) {
+      return Calculate(SymbolicDataAnalysisTreeInterpreter, tree, LowerEstimationLimit.Value, UpperEstimationLimit.Value, problemData, rows);
+    }
   }
 }
Index: branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveValidationBestSolutionAnalyzer.cs
===================================================================
--- branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveValidationBestSolutionAnalyzer.cs	(revision 5607)
+++ branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveValidationBestSolutionAnalyzer.cs	(revision 5607)
@@ -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.Collections.Generic;
+using System.Linq;
+using HeuristicLab.Common;
+using HeuristicLab.Core;
+using HeuristicLab.Data;
+using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
+using HeuristicLab.Operators;
+using HeuristicLab.Optimization;
+using HeuristicLab.Parameters;
+using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
+
+namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression {
+  /// <summary>
+  /// An operator that analyzes the validation best symbolic regression solution for single objective symbolic regression problems.
+  /// </summary>
+  [Item("SymbolicRegressionSingleObjectiveValidationBestSolutionAnalyzer", "An operator that analyzes the validation best symbolic regression solution for single objective symbolic regression problems.")]
+  [StorableClass]
+  public sealed class SymbolicRegressionSingleObjectiveValidationBestSolutionAnalyzer : SymbolicDataAnalysisSingleObjectiveValidationBestSolutionAnalyzer<ISymbolicRegressionSolution, ISymbolicRegressionEvaluator, IRegressionProblemData> {
+    [StorableConstructor]
+    private SymbolicRegressionSingleObjectiveValidationBestSolutionAnalyzer(bool deserializing) : base(deserializing) { }
+    private SymbolicRegressionSingleObjectiveValidationBestSolutionAnalyzer(SymbolicRegressionSingleObjectiveValidationBestSolutionAnalyzer original, Cloner cloner) : base(original, cloner) { }
+    public SymbolicRegressionSingleObjectiveValidationBestSolutionAnalyzer()
+      : base() {
+    }
+    public override IDeepCloneable Clone(Cloner cloner) {
+      return new SymbolicRegressionSingleObjectiveValidationBestSolutionAnalyzer(this, cloner);
+    }
+
+    protected override ISymbolicRegressionSolution CreateSolution(ISymbolicExpressionTree bestTree, double bestQuality) {
+      throw new System.NotImplementedException();
+    }
+  }
+}
Index: branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SymbolicRegressionSolution.cs
===================================================================
--- branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SymbolicRegressionSolution.cs	(revision 5607)
+++ branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SymbolicRegressionSolution.cs	(revision 5607)
@@ -0,0 +1,89 @@
+#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.Collections.Generic;
+using System.Linq;
+using HeuristicLab.Common;
+using HeuristicLab.Core;
+using HeuristicLab.Data;
+using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
+using HeuristicLab.Operators;
+using HeuristicLab.Parameters;
+using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
+using HeuristicLab.Optimization;
+using System;
+
+namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
+  /// <summary>
+  /// Represents a symbolic regression solution (model + data) and attributes of the solution like accuracy and complexity
+  /// </summary>
+  [StorableClass]
+  [Item(Name = "SymbolicRegressionSolution", Description = "Represents a symbolic regression solution (model + data) and attributes of the solution like accuracy and complexity.")]
+  public class SymbolicRegressionSolution : SymbolicDataAnalysisSolution, IRegressionSolution {
+    #region properties
+    public new IRegressionModel Model {
+      get { throw new NotImplementedException(); }
+    }
+
+    public new IRegressionProblemData ProblemData {
+      get { throw new NotImplementedException(); }
+    }
+
+    public IEnumerable<double> EstimatedValues {
+      get { throw new NotImplementedException(); }
+    }
+
+    public IEnumerable<double> EstimatedTrainingValues {
+      get { throw new NotImplementedException(); }
+    }
+
+    public IEnumerable<double> EstimatedTestValues {
+      get { throw new NotImplementedException(); }
+    }
+
+    public IEnumerable<double> GetEstimatedValues(IEnumerable<int> rows) {
+      throw new NotImplementedException();
+    }
+
+    #endregion
+
+    [StorableConstructor]
+    protected SymbolicRegressionSolution(bool deserializing) : base(deserializing) { }
+    protected SymbolicRegressionSolution(SymbolicRegressionSolution original, Cloner cloner)
+      : base(original, cloner) {
+    }
+    public SymbolicRegressionSolution()
+      : base() {
+    }
+
+    public override IDeepCloneable Clone(Cloner cloner) {
+      return new SymbolicRegressionSolution(this, cloner);
+    }
+
+    protected override void OnModelChanged(EventArgs e) {
+      base.OnModelChanged(e);
+    }
+
+    protected override void OnProblemDataChanged(EventArgs e) {
+      base.OnProblemDataChanged(e);
+    }
+  }
+}
