Index: trunk/sources/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/Analyzers/SymbolicRegressionModelQualityAnalyzer.cs
===================================================================
--- trunk/sources/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/Analyzers/SymbolicRegressionModelQualityAnalyzer.cs	(revision 3996)
+++ trunk/sources/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/Analyzers/SymbolicRegressionModelQualityAnalyzer.cs	(revision 4054)
@@ -91,8 +91,4 @@
     private const string RelativeErrorValuesParameterName = "Average relative error";
 
-    private const string TrainingSamplesStartParameterName = "TrainingSamplesStart";
-    private const string TrainingSamplesEndParameterName = "TrainingSamplesEnd";
-    private const string TestSamplesStartParameterName = "TestSamplesStart";
-    private const string TestSamplesEndParameterName = "TestSamplesEnd";
     private const string UpperEstimationLimitParameterName = "UpperEstimationLimit";
     private const string LowerEstimationLimitParameterName = "LowerEstimationLimit";
@@ -107,16 +103,4 @@
     public IValueLookupParameter<DataAnalysisProblemData> ProblemDataParameter {
       get { return (IValueLookupParameter<DataAnalysisProblemData>)Parameters[ProblemDataParameterName]; }
-    }
-    public IValueLookupParameter<IntValue> TrainingSamplesStartParameter {
-      get { return (IValueLookupParameter<IntValue>)Parameters[TrainingSamplesStartParameterName]; }
-    }
-    public IValueLookupParameter<IntValue> TrainingSamplesEndParameter {
-      get { return (IValueLookupParameter<IntValue>)Parameters[TrainingSamplesEndParameterName]; }
-    }
-    public IValueLookupParameter<IntValue> TestSamplesStartParameter {
-      get { return (IValueLookupParameter<IntValue>)Parameters[TestSamplesStartParameterName]; }
-    }
-    public IValueLookupParameter<IntValue> TestSamplesEndParameter {
-      get { return (IValueLookupParameter<IntValue>)Parameters[TestSamplesEndParameterName]; }
     }
     public IValueLookupParameter<DoubleValue> UpperEstimationLimitParameter {
@@ -144,8 +128,4 @@
       Parameters.Add(new ValueLookupParameter<ISymbolicExpressionTreeInterpreter>(SymbolicExpressionTreeInterpreterParameterName, "The interpreter that should be used to calculate the output values of the symbolic expression tree."));
       Parameters.Add(new ValueLookupParameter<DataAnalysisProblemData>(ProblemDataParameterName, "The problem data containing the input varaibles for the symbolic regression problem."));
-      Parameters.Add(new ValueLookupParameter<IntValue>(TrainingSamplesStartParameterName, "The first index of the training data set partition on which the model quality values should be calculated."));
-      Parameters.Add(new ValueLookupParameter<IntValue>(TrainingSamplesEndParameterName, "The last index of the training data set partition on which the model quality values should be calculated."));
-      Parameters.Add(new ValueLookupParameter<IntValue>(TestSamplesStartParameterName, "The first index of the test data set partition on which the model quality values should be calculated."));
-      Parameters.Add(new ValueLookupParameter<IntValue>(TestSamplesEndParameterName, "The last index of the test data set partition on which the model quality values should be calculated."));
       Parameters.Add(new ValueLookupParameter<DoubleValue>(UpperEstimationLimitParameterName, "The upper limit that should be used as cut off value for the output values of symbolic expression trees."));
       Parameters.Add(new ValueLookupParameter<DoubleValue>(LowerEstimationLimitParameterName, "The lower limit that should be used as cut off value for the output values of symbolic expression trees."));
@@ -162,6 +142,6 @@
       Analyze(SymbolicExpressionTreeParameter.ActualValue, SymbolicExpressionTreeInterpreterParameter.ActualValue,
         UpperEstimationLimit.Value, LowerEstimationLimit.Value, ProblemDataParameter.ActualValue,
-        TrainingSamplesStartParameter.ActualValue.Value, TrainingSamplesEndParameter.ActualValue.Value,
-        TestSamplesStartParameter.ActualValue.Value, TestSamplesEndParameter.ActualValue.Value,
+        ProblemDataParameter.ActualValue.TrainingSamplesStart.Value, ProblemDataParameter.ActualValue.TrainingSamplesEnd.Value,
+        ProblemDataParameter.ActualValue.TestSamplesStart.Value, ProblemDataParameter.ActualValue.TestSamplesEnd.Value,
         ResultsParameter.ActualValue);
       return base.Apply();
