Index: trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/KernelRidgeRegression/KernelFunctions/CicularKernel.cs
===================================================================
--- trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/KernelRidgeRegression/KernelFunctions/CicularKernel.cs	(revision 15157)
+++ trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/KernelRidgeRegression/KernelFunctions/CicularKernel.cs	(revision 15158)
@@ -41,4 +41,5 @@
 
     protected override double Get(double norm) {
+      if (Beta == null) throw new InvalidOperationException("Can not calculate kernel distance while Beta is null");
       var beta = Beta.Value;
       if (Math.Abs(beta) < double.Epsilon) return double.NaN;
@@ -50,4 +51,5 @@
     // 4*pi*n^3 / (beta^4 * sqrt(1-n^2/beta^2) 
     protected override double GetGradient(double norm) {
+      if (Beta == null) throw new InvalidOperationException("Can not calculate kernel distance gradient while Beta is null");
       var beta = Beta.Value;
       if (Math.Abs(beta) < double.Epsilon) return double.NaN;
Index: trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/KernelRidgeRegression/KernelFunctions/GaussianKernel.cs
===================================================================
--- trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/KernelRidgeRegression/KernelFunctions/GaussianKernel.cs	(revision 15157)
+++ trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/KernelRidgeRegression/KernelFunctions/GaussianKernel.cs	(revision 15158)
@@ -44,4 +44,5 @@
 
     protected override double Get(double norm) {
+      if (Beta == null) throw new InvalidOperationException("Can not calculate kernel distance while Beta is null");
       var beta = Beta.Value;
       if (Math.Abs(beta) < double.Epsilon) return double.NaN;
@@ -52,4 +53,5 @@
     //2 * n²/b²* 1/b * exp(-n²/b²)
     protected override double GetGradient(double norm) {
+      if (Beta == null) throw new InvalidOperationException("Can not calculate kernel distance gradient while Beta is null");
       var beta = Beta.Value;
       if (Math.Abs(beta) < double.Epsilon) return double.NaN;
Index: trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/KernelRidgeRegression/KernelFunctions/InverseMultiquadraticKernel.cs
===================================================================
--- trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/KernelRidgeRegression/KernelFunctions/InverseMultiquadraticKernel.cs	(revision 15157)
+++ trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/KernelRidgeRegression/KernelFunctions/InverseMultiquadraticKernel.cs	(revision 15158)
@@ -43,4 +43,5 @@
 
     protected override double Get(double norm) {
+      if (Beta == null) throw new InvalidOperationException("Can not calculate kernel distance while Beta is null");
       var beta = Beta.Value;
       if (Math.Abs(beta) < double.Epsilon) return double.NaN;
@@ -51,4 +52,5 @@
     //n²/(b³(n²/b² + C)^1.5)
     protected override double GetGradient(double norm) {
+      if (Beta == null) throw new InvalidOperationException("Can not calculate kernel distance gradient while Beta is null");
       var beta = Beta.Value;
       if (Math.Abs(beta) < double.Epsilon) return double.NaN;
Index: trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/KernelRidgeRegression/KernelFunctions/MultiquadraticKernel.cs
===================================================================
--- trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/KernelRidgeRegression/KernelFunctions/MultiquadraticKernel.cs	(revision 15157)
+++ trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/KernelRidgeRegression/KernelFunctions/MultiquadraticKernel.cs	(revision 15158)
@@ -36,6 +36,5 @@
     protected MultiquadraticKernel(bool deserializing) : base(deserializing) { }
 
-    protected MultiquadraticKernel(MultiquadraticKernel original, Cloner cloner)
-                : base(original, cloner) { }
+    protected MultiquadraticKernel(MultiquadraticKernel original, Cloner cloner) : base(original, cloner) { }
 
     public MultiquadraticKernel() { }
@@ -46,4 +45,5 @@
 
     protected override double Get(double norm) {
+      if (Beta == null) throw new InvalidOperationException("Can not calculate kernel distance while Beta is null");
       var beta = Beta.Value;
       if (Math.Abs(beta) < double.Epsilon) return double.NaN;
@@ -54,4 +54,5 @@
     //-n²/(d³*sqrt(C+n²/d²))
     protected override double GetGradient(double norm) {
+      if (Beta == null) throw new InvalidOperationException("Can not calculate kernel distance gradient while Beta is null");
       var beta = Beta.Value;
       if (Math.Abs(beta) < double.Epsilon) return double.NaN;
Index: trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/KernelRidgeRegression/KernelFunctions/PolysplineKernel.cs
===================================================================
--- trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/KernelRidgeRegression/KernelFunctions/PolysplineKernel.cs	(revision 15157)
+++ trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/KernelRidgeRegression/KernelFunctions/PolysplineKernel.cs	(revision 15158)
@@ -57,4 +57,5 @@
 
     protected override double Get(double norm) {
+      if (Beta == null) throw new InvalidOperationException("Can not calculate kernel distance while Beta is null");
       var beta = Beta.Value;
       if (Math.Abs(beta) < double.Epsilon) return double.NaN;
@@ -65,4 +66,5 @@
     //-degree/beta * (norm/beta)^degree
     protected override double GetGradient(double norm) {
+      if (Beta == null) throw new InvalidOperationException("Can not calculate kernel distance gradient while Beta is null");
       var beta = Beta.Value;
       if (Math.Abs(beta) < double.Epsilon) return double.NaN;
Index: trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/KernelRidgeRegression/KernelFunctions/ThinPlatePolysplineKernel.cs
===================================================================
--- trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/KernelRidgeRegression/KernelFunctions/ThinPlatePolysplineKernel.cs	(revision 15157)
+++ trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/KernelRidgeRegression/KernelFunctions/ThinPlatePolysplineKernel.cs	(revision 15158)
@@ -56,4 +56,5 @@
 
     protected override double Get(double norm) {
+      if (Beta == null) throw new InvalidOperationException("Can not calculate kernel distance while Beta is null");
       var beta = Beta.Value;
       if (Math.Abs(beta) < double.Epsilon) return double.NaN;
@@ -65,4 +66,5 @@
     // (Degree/beta) * (norm/beta)^Degree * log(norm/beta) 
     protected override double GetGradient(double norm) {
+      if (Beta == null) throw new InvalidOperationException("Can not calculate kernel distance while Beta is null");
       var beta = Beta.Value;
       if (Math.Abs(beta) < double.Epsilon) return double.NaN;
