Index: stable/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/MeanFunctions/MeanConst.cs
===================================================================
--- stable/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/MeanFunctions/MeanConst.cs	(revision 13400)
+++ stable/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/MeanFunctions/MeanConst.cs	(revision 13981)
@@ -76,5 +76,5 @@
     }
 
-    public ParameterizedMeanFunction GetParameterizedMeanFunction(double[] p, IEnumerable<int> columnIndices) {
+    public ParameterizedMeanFunction GetParameterizedMeanFunction(double[] p, int[] columnIndices) {
       double c;
       GetParameters(p, out c);
Index: stable/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/MeanFunctions/MeanLinear.cs
===================================================================
--- stable/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/MeanFunctions/MeanLinear.cs	(revision 13400)
+++ stable/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/MeanFunctions/MeanLinear.cs	(revision 13981)
@@ -21,5 +21,4 @@
 
 using System;
-using System.Collections.Generic;
 using System.Linq;
 using HeuristicLab.Common;
@@ -70,7 +69,7 @@
     }
 
-    public ParameterizedMeanFunction GetParameterizedMeanFunction(double[] p, IEnumerable<int> columnIndices) {
+    public ParameterizedMeanFunction GetParameterizedMeanFunction(double[] p, int[] columnIndices) {
       double[] weights;
-      int[] columns = columnIndices.ToArray();
+      int[] columns = columnIndices;
       GetParameter(p, out weights);
       var mf = new ParameterizedMeanFunction();
@@ -78,5 +77,5 @@
         // sanity check
         if (weights.Length != columns.Length) throw new ArgumentException("The number of rparameters must match the number of variables for the linear mean function.");
-        return Util.ScalarProd(weights, Util.GetRow(x, i, columns));
+        return Util.ScalarProd(weights, Util.GetRow(x, i, columns).ToArray());
       };
       mf.Gradient = (x, i, k) => {
Index: stable/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/MeanFunctions/MeanModel.cs
===================================================================
--- stable/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/MeanFunctions/MeanModel.cs	(revision 13400)
+++ stable/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/MeanFunctions/MeanModel.cs	(revision 13981)
@@ -73,9 +73,9 @@
     }
 
-    public ParameterizedMeanFunction GetParameterizedMeanFunction(double[] p, IEnumerable<int> columnIndices) {
+    public ParameterizedMeanFunction GetParameterizedMeanFunction(double[] p, int[] columnIndices) {
       if (p.Length > 0) throw new ArgumentException("No parameters allowed for model-based mean function.", "p");
       var solution = RegressionSolution;
       var variableNames = solution.ProblemData.AllowedInputVariables.ToArray();
-      if (variableNames.Length != columnIndices.Count())
+      if (variableNames.Length != columnIndices.Length)
         throw new ArgumentException("The number of input variables does not match in MeanModel");
       var variableValues = variableNames.Select(_ => new List<double>() { 0.0 }).ToArray(); // or of zeros
Index: stable/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/MeanFunctions/MeanProduct.cs
===================================================================
--- stable/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/MeanFunctions/MeanProduct.cs	(revision 13400)
+++ stable/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/MeanFunctions/MeanProduct.cs	(revision 13981)
@@ -73,5 +73,5 @@
 
 
-    public ParameterizedMeanFunction GetParameterizedMeanFunction(double[] p, IEnumerable<int> columnIndices) {
+    public ParameterizedMeanFunction GetParameterizedMeanFunction(double[] p, int[] columnIndices) {
       var factorMf = new List<ParameterizedMeanFunction>();
       int totalNumberOfParameters = GetNumberOfParameters(numberOfVariables);
Index: stable/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/MeanFunctions/MeanSum.cs
===================================================================
--- stable/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/MeanFunctions/MeanSum.cs	(revision 13400)
+++ stable/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/MeanFunctions/MeanSum.cs	(revision 13981)
@@ -68,5 +68,5 @@
     }
 
-    public ParameterizedMeanFunction GetParameterizedMeanFunction(double[] p, IEnumerable<int> columnIndices) {
+    public ParameterizedMeanFunction GetParameterizedMeanFunction(double[] p, int[] columnIndices) {
       var termMf = new List<ParameterizedMeanFunction>();
       int totalNumberOfParameters = GetNumberOfParameters(numberOfVariables);
Index: stable/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/MeanFunctions/MeanZero.cs
===================================================================
--- stable/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/MeanFunctions/MeanZero.cs	(revision 13400)
+++ stable/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/MeanFunctions/MeanZero.cs	(revision 13981)
@@ -20,6 +20,4 @@
 #endregion
 using System;
-using System.Collections.Generic;
-using System.Linq;
 using HeuristicLab.Common;
 using HeuristicLab.Core;
@@ -50,5 +48,5 @@
     }
 
-    public ParameterizedMeanFunction GetParameterizedMeanFunction(double[] p, IEnumerable<int> columnIndices) {
+    public ParameterizedMeanFunction GetParameterizedMeanFunction(double[] p, int[] columnIndices) {
       if (p.Length > 0) throw new ArgumentException("No parameters allowed for zero mean function.", "p");
       var mf = new ParameterizedMeanFunction();
