Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman1.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman1.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman1.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("I.6.20a exp(-theta**2/2)/sqrt(2*pi) | {0} samples | {1}", trainingSamples,
+        return string.Format("I.6.20a exp(-theta**2/2)/sqrt(2*pi) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -62,5 +62,5 @@
       if (noiseRatio != null) {
         var f_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * f.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * f.StandardDeviationPop();
         f_noise.AddRange(f.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(f);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman10.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman10.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman10.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("I.12.4 q1/(4*pi*epsilon*r**2) | {0} samples | {1}", trainingSamples,
+        return string.Format("I.12.4 q1/(4*pi*epsilon*r**2) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -70,5 +70,5 @@
       if (noiseRatio != null) {
         var Ef_noise    = new List<double>();
-        var sigma_noise = (double) noiseRatio * Ef.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * Ef.StandardDeviationPop();
         Ef_noise.AddRange(Ef.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(Ef);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman100.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman100.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman100.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("III.21.20 -rho_c_0*q*A_vec/m | {0} samples | {1}", trainingSamples,
+        return string.Format("III.21.20 -rho_c_0*q*A_vec/m | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -72,5 +72,5 @@
       if (noiseRatio != null) {
         var j_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * j.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * j.StandardDeviationPop();
         j_noise.AddRange(j.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(j);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman11.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman11.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman11.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("I.12.5 q2*Ef | {0} samples | {1}", trainingSamples,
+        return string.Format("I.12.5 q2*Ef | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -68,5 +68,5 @@
       if (noiseRatio != null) {
         var F_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * F.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * F.StandardDeviationPop();
         F_noise.AddRange(F.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(F);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman12.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman12.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman12.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("I.12.11 q*(Ef + B*v*sin(theta)) | {0} samples | {1}", trainingSamples,
+        return string.Format("I.12.11 q*(Ef + B*v*sin(theta)) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -74,5 +74,5 @@
       if (noiseRatio != null) {
         var F_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * F.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * F.StandardDeviationPop();
         F_noise.AddRange(F.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(F);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman13.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman13.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman13.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("I.13.4 1/2*m*(v**2+u**2+w**2) | {0} samples | {1}", trainingSamples,
+        return string.Format("I.13.4 1/2*m*(v**2+u**2+w**2) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -72,5 +72,5 @@
       if (noiseRatio != null) {
         var K_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * K.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * K.StandardDeviationPop();
         K_noise.AddRange(K.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(K);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman14.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman14.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman14.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("I.13.12 G*m1*m2*(1/r2-1/r1) | {0} samples | {1}", trainingSamples,
+        return string.Format("I.13.12 G*m1*m2*(1/r2-1/r1) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -74,5 +74,5 @@
       if (noiseRatio != null) {
         var U_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * U.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * U.StandardDeviationPop();
         U_noise.AddRange(U.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(U);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman15.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman15.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman15.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("I.14.3 m*g*z | {0} samples | {1}", trainingSamples,
+        return string.Format("I.14.3 m*g*z | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -70,5 +70,5 @@
       if (noiseRatio != null) {
         var U_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * U.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * U.StandardDeviationPop();
         U_noise.AddRange(U.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(U);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman16.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman16.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman16.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("I.14.4 1/2*k_spring*x**2 | {0} samples | {1}", trainingSamples,
+        return string.Format("I.14.4 1/2*k_spring*x**2 | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -68,5 +68,5 @@
       if (noiseRatio != null) {
         var U_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * U.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * U.StandardDeviationPop();
         U_noise.AddRange(U.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(U);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman17.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman17.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman17.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("I.15.3x (x-u*t)/sqrt(1-u**2/c**2) | {0} samples | {1}", trainingSamples,
+        return string.Format("I.15.3x (x-u*t)/sqrt(1-u**2/c**2) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -72,5 +72,5 @@
       if (noiseRatio != null) {
         var x1_noise    = new List<double>();
-        var sigma_noise = (double) noiseRatio * x1.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * x1.StandardDeviationPop();
         x1_noise.AddRange(x1.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(x1);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman18.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman18.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman18.cs	(revision 17805)
@@ -28,6 +28,6 @@
     public override string Name {
       get {
-        return string.Format("I.15.3t (t-u*x/c**2)/sqrt(1-u**2/c**2) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+        return string.Format("I.15.3t (t-u*x/c**2)/sqrt(1-u**2/c**2) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -72,5 +72,5 @@
       if (noiseRatio != null) {
         var t1_noise    = new List<double>();
-        var sigma_noise = (double) noiseRatio * t1.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * t1.StandardDeviationPop();
         t1_noise.AddRange(t1.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(t1);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman19.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman19.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman19.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("I.15.10 m_0*v/sqrt(1-v**2/c**2) | {0} samples | {1}", trainingSamples,
+        return string.Format("I.15.10 m_0*v/sqrt(1-v**2/c**2) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -70,5 +70,5 @@
       if (noiseRatio != null) {
         var p_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * p.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * p.StandardDeviationPop();
         p_noise.AddRange(p.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(p);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman2.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman2.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman2.cs	(revision 17805)
@@ -28,6 +28,6 @@
     public override string Name {
       get {
-        return string.Format("I.6.20 exp(-(theta/sigma)**2/2)/(sqrt(2*pi)*sigma) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+        return string.Format("I.6.20 exp(-(theta/sigma)**2/2)/(sqrt(2*pi)*sigma) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -68,5 +68,5 @@
       if (noiseRatio != null) {
         var f_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * f.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * f.StandardDeviationPop();
         f_noise.AddRange(f.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(f);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman20.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman20.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman20.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("I.16.6 (u+v)/(1+u*v/c**2) | {0} samples | {1}", trainingSamples,
+        return string.Format("I.16.6 (u+v)/(1+u*v/c**2) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -70,5 +70,5 @@
       if (noiseRatio != null) {
         var v1_noise    = new List<double>();
-        var sigma_noise = (double) noiseRatio * v1.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * v1.StandardDeviationPop();
         v1_noise.AddRange(v1.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(v1);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman21.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman21.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman21.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("I.18.4 (m1*r1 + m2*r2)/(m1 + m2) | {0} samples | {1}", trainingSamples,
+        return string.Format("I.18.4 (m1*r1 + m2*r2)/(m1 + m2) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -72,5 +72,5 @@
       if (noiseRatio != null) {
         var r_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * r.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * r.StandardDeviationPop();
         r_noise.AddRange(r.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(r);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman22.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman22.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman22.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("I.18.12 r*F*sin(theta) | {0} samples | {1}", trainingSamples,
+        return string.Format("I.18.12 r*F*sin(theta) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -70,5 +70,5 @@
       if (noiseRatio != null) {
         var tau_noise   = new List<double>();
-        var sigma_noise = (double) noiseRatio * tau.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * tau.StandardDeviationPop();
         tau_noise.AddRange(tau.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(tau);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman23.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman23.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman23.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("I.18.16 m*r*v*sin(theta) | {0} samples | {1}", trainingSamples,
+        return string.Format("I.18.16 m*r*v*sin(theta) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -72,5 +72,5 @@
       if (noiseRatio != null) {
         var L_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * L.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * L.StandardDeviationPop();
         L_noise.AddRange(L.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(L);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman24.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman24.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman24.cs	(revision 17805)
@@ -28,6 +28,6 @@
     public override string Name {
       get {
-        return string.Format("I.24.6 1/4*m*(omega**2 + omega_0**2)*x**2 | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+        return string.Format("I.24.6 1/4*m*(omega**2 + omega_0**2)*x**2 | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -72,5 +72,5 @@
       if (noiseRatio != null) {
         var E_n_noise   = new List<double>();
-        var sigma_noise = (double) noiseRatio * E_n.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * E_n.StandardDeviationPop();
         E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(E_n);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman25.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman25.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman25.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("I.25.13 q/C | {0} samples | {1}", trainingSamples,
+        return string.Format("I.25.13 q/C | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -68,5 +68,5 @@
       if (noiseRatio != null) {
         var Volt_noise  = new List<double>();
-        var sigma_noise = (double) noiseRatio * Volt.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * Volt.StandardDeviationPop();
         Volt_noise.AddRange(Volt.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(Volt);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman26.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman26.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman26.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("I.26.2 arcsin(n*sin(theta2)) | {0} samples | {1}", trainingSamples,
+        return string.Format("I.26.2 arcsin(n*sin(theta2)) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -68,5 +68,5 @@
       if (noiseRatio != null) {
         var theta1_noise = new List<double>();
-        var sigma_noise  = (double) noiseRatio * theta1.StandardDeviationPop();
+        var sigma_noise  = (double) Math.Sqrt(noiseRatio.Value) * theta1.StandardDeviationPop();
         theta1_noise.AddRange(theta1.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(theta1);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman27.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman27.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman27.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("I.27.6 1/(1/d1+n/d2) | {0} samples | {1}", trainingSamples,
+        return string.Format("I.27.6 1/(1/d1+n/d2) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -70,5 +70,5 @@
       if (noiseRatio != null) {
         var foc_noise   = new List<double>();
-        var sigma_noise = (double) noiseRatio * foc.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * foc.StandardDeviationPop();
         foc_noise.AddRange(foc.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(foc);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman28.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman28.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman28.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("I.29.4 omega/c | {0} samples | {1}", trainingSamples,
+        return string.Format("I.29.4 omega/c | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -68,5 +68,5 @@
       if (noiseRatio != null) {
         var k_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * k.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * k.StandardDeviationPop();
         k_noise.AddRange(k.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(k);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman29.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman29.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman29.cs	(revision 17805)
@@ -28,6 +28,6 @@
     public override string Name {
       get {
-        return string.Format("I.29.16 sqrt(x1**2+x2**2 - 2*x1*x2*cos(theta1 - theta2)) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+        return string.Format("I.29.16 sqrt(x1**2+x2**2 - 2*x1*x2*cos(theta1 - theta2)) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -73,5 +73,5 @@
       if (noiseRatio != null) {
         var x_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * x.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * x.StandardDeviationPop();
         x_noise.AddRange(x.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(x);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman3.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman3.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman3.cs	(revision 17805)
@@ -29,6 +29,6 @@
       get {
         return string.Format(
-          "I.6.20b exp(-((theta-theta1)/sigma)**2/2)/(sqrt(2*pi)*sigma) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+          "I.6.20b exp(-((theta-theta1)/sigma)**2/2)/(sqrt(2*pi)*sigma) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -71,5 +71,5 @@
       if (noiseRatio != null) {
         var f_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * f.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * f.StandardDeviationPop();
         f_noise.AddRange(f.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(f);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman30.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman30.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman30.cs	(revision 17805)
@@ -28,6 +28,6 @@
     public override string Name {
       get {
-        return string.Format("I.30.3 Int_0*sin(n*theta/2)**2/sin(theta/2)**2 | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+        return string.Format("I.30.3 Int_0*sin(n*theta/2)**2/sin(theta/2)**2 | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -70,5 +70,5 @@
       if (noiseRatio != null) {
         var Int_noise   = new List<double>();
-        var sigma_noise = (double) noiseRatio * Int.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * Int.StandardDeviationPop();
         Int_noise.AddRange(Int.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(Int);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman31.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman31.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman31.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("I.30.5 arcsin(lambd/(n*d)) | {0} samples | {1}", trainingSamples,
+        return string.Format("I.30.5 arcsin(lambd/(n*d)) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -70,5 +70,5 @@
       if (noiseRatio != null) {
         var theta_noise = new List<double>();
-        var sigma_noise = (double) noiseRatio * theta.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * theta.StandardDeviationPop();
         theta_noise.AddRange(theta.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(theta);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman32.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman32.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman32.cs	(revision 17805)
@@ -28,6 +28,6 @@
     public override string Name {
       get {
-        return string.Format("I.32.5 q**2*a**2/(6*pi*epsilon*c**3) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+        return string.Format("I.32.5 q**2*a**2/(6*pi*epsilon*c**3) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -72,5 +72,5 @@
       if (noiseRatio != null) {
         var Pwr_noise   = new List<double>();
-        var sigma_noise = (double) noiseRatio * Pwr.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * Pwr.StandardDeviationPop();
         Pwr_noise.AddRange(Pwr.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(Pwr);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman33.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman33.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman33.cs	(revision 17805)
@@ -29,6 +29,6 @@
       get {
         return string.Format(
-          "I.32.17 (1/2*epsilon*c*Ef**2)*(8*pi*r**2/3)*(omega**4/(omega**2-omega_0**2)**2) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+          "I.32.17 (1/2*epsilon*c*Ef**2)*(8*pi*r**2/3)*(omega**4/(omega**2-omega_0**2)**2) | {0}",
+            noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -80,5 +80,5 @@
       if (noiseRatio != null) {
         var Pwr_noise   = new List<double>();
-        var sigma_noise = (double) noiseRatio * Pwr.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * Pwr.StandardDeviationPop();
         Pwr_noise.AddRange(Pwr.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(Pwr);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman34.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman34.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman34.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("I.34.8 q*v*B/p | {0} samples | {1}", trainingSamples,
+        return string.Format("I.34.8 q*v*B/p | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -72,5 +72,5 @@
       if (noiseRatio != null) {
         var omega_noise = new List<double>();
-        var sigma_noise = (double) noiseRatio * omega.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * omega.StandardDeviationPop();
         omega_noise.AddRange(omega.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(omega);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman35.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman35.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman35.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("I.34.10 omega_0/(1-v/c) | {0} samples | {1}", trainingSamples,
+        return string.Format("I.34.10 omega_0/(1-v/c) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -70,5 +70,5 @@
       if (noiseRatio != null) {
         var omega_noise = new List<double>();
-        var sigma_noise = (double) noiseRatio * omega.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * omega.StandardDeviationPop();
         omega_noise.AddRange(omega.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(omega);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman36.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman36.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman36.cs	(revision 17805)
@@ -28,6 +28,6 @@
     public override string Name {
       get {
-        return string.Format("I.34.14 (1+v/c)/sqrt(1-v**2/c**2)*omega_0 | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+        return string.Format("I.34.14 (1+v/c)/sqrt(1-v**2/c**2)*omega_0 | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -70,5 +70,5 @@
       if (noiseRatio != null) {
         var omega_noise = new List<double>();
-        var sigma_noise = (double) noiseRatio * omega.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * omega.StandardDeviationPop();
         omega_noise.AddRange(omega.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(omega);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman37.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman37.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman37.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("I.34.27 h*omega | {0} samples | {1}", trainingSamples,
+        return string.Format("I.34.27 h*omega | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -68,5 +68,5 @@
       if (noiseRatio != null) {
         var E_n_noise   = new List<double>();
-        var sigma_noise = (double) noiseRatio * E_n.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * E_n.StandardDeviationPop();
         E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(E_n);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman38.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman38.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman38.cs	(revision 17805)
@@ -28,6 +28,6 @@
     public override string Name {
       get {
-        return string.Format("I.37.4 I1 + I2 + 2*sqrt(I1*I2)*cos(delta) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+        return string.Format("I.37.4 I1 + I2 + 2*sqrt(I1*I2)*cos(delta) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -70,5 +70,5 @@
       if (noiseRatio != null) {
         var Int_noise   = new List<double>();
-        var sigma_noise = (double) noiseRatio * Int.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * Int.StandardDeviationPop();
         Int_noise.AddRange(Int.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(Int);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman39.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman39.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman39.cs	(revision 17805)
@@ -28,6 +28,6 @@
     public override string Name {
       get {
-        return string.Format("I.38.12 4*pi*epsilon*h**2/(m*q**2) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+        return string.Format("I.38.12 4*pi*epsilon*h**2/(m*q**2) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -72,5 +72,5 @@
       if (noiseRatio != null) {
         var r_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * r.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * r.StandardDeviationPop();
         r_noise.AddRange(r.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(r);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman4.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman4.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman4.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("I.8.14 sqrt((x2-x1)**2+(y2-y1)**2) | {0} samples | {1}", trainingSamples,
+        return string.Format("I.8.14 sqrt((x2-x1)**2+(y2-y1)**2) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -72,5 +72,5 @@
       if (noiseRatio != null) {
         var d_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * d.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * d.StandardDeviationPop();
         d_noise.AddRange(d.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(d);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman40.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman40.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman40.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("I.39.10 3/2*pF*V | {0} samples | {1}", trainingSamples,
+        return string.Format("I.39.10 3/2*pF*V | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -68,5 +68,5 @@
       if (noiseRatio != null) {
         var E_n_noise   = new List<double>();
-        var sigma_noise = (double) noiseRatio * E_n.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * E_n.StandardDeviationPop();
         E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(E_n);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman41.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman41.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman41.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("I.39.11 1/(gamma-1)*pF*V | {0} samples | {1}", trainingSamples,
+        return string.Format("I.39.11 1/(gamma-1)*pF*V | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -70,5 +70,5 @@
       if (noiseRatio != null) {
         var E_n_noise   = new List<double>();
-        var sigma_noise = (double) noiseRatio * E_n.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * E_n.StandardDeviationPop();
         E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(E_n);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman42.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman42.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman42.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("I.39.22 n*kb*T/V | {0} samples | {1}", trainingSamples,
+        return string.Format("I.39.22 n*kb*T/V | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -72,5 +72,5 @@
       if (noiseRatio != null) {
         var pr_noise    = new List<double>();
-        var sigma_noise = (double) noiseRatio * pr.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * pr.StandardDeviationPop();
         pr_noise.AddRange(pr.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(pr);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman43.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman43.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman43.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("I.40.1 n_0*exp(-m*g*x/(kb*T)) | {0} samples | {1}", trainingSamples,
+        return string.Format("I.40.1 n_0*exp(-m*g*x/(kb*T)) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -76,5 +76,5 @@
       if (noiseRatio != null) {
         var n_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * n.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * n.StandardDeviationPop();
         n_noise.AddRange(n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(n);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman44.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman44.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman44.cs	(revision 17805)
@@ -29,6 +29,6 @@
       get {
         return string.Format(
-          "I.41.16 h*omega**3/(pi**2 * c**2 * (exp(h*omega/(kb*T))-1)) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+          "I.41.16 h*omega**3/(pi**2 * c**2 * (exp(h*omega/(kb*T))-1)) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -77,5 +77,5 @@
       if (noiseRatio != null) {
         var L_rad_noise = new List<double>();
-        var sigma_noise = (double) noiseRatio * L_rad.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * L_rad.StandardDeviationPop();
         L_rad_noise.AddRange(L_rad.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(L_rad);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman45.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman45.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman45.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("I.43.16 mu_drift*q*Volt/d | {0} samples | {1}", trainingSamples,
+        return string.Format("I.43.16 mu_drift*q*Volt/d | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -72,5 +72,5 @@
       if (noiseRatio != null) {
         var v_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * v.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * v.StandardDeviationPop();
         v_noise.AddRange(v.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(v);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman46.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman46.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman46.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("I.43.31 mob*kb*T | {0} samples | {1}", trainingSamples,
+        return string.Format("I.43.31 mob*kb*T | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -70,5 +70,5 @@
       if (noiseRatio != null) {
         var D_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * D.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * D.StandardDeviationPop();
         D_noise.AddRange(D.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(D);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman47.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman47.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman47.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("I.43.43 1/(gamma-1)*kb*v/A | {0} samples | {1}", trainingSamples,
+        return string.Format("I.43.43 1/(gamma-1)*kb*v/A | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -72,5 +72,5 @@
       if (noiseRatio != null) {
         var kappa_noise = new List<double>();
-        var sigma_noise = (double) noiseRatio * kappa.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * kappa.StandardDeviationPop();
         kappa_noise.AddRange(kappa.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(kappa);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman48.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman48.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman48.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("I.44.4 n*kb*T*ln(V2/V1) | {0} samples | {1}", trainingSamples,
+        return string.Format("I.44.4 n*kb*T*ln(V2/V1) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -74,5 +74,5 @@
       if (noiseRatio != null) {
         var E_n_noise   = new List<double>();
-        var sigma_noise = (double) noiseRatio * E_n.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * E_n.StandardDeviationPop();
         E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(E_n);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman49.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman49.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman49.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("I.47.23 sqrt(gamma*pr/rho) | {0} samples | {1}", trainingSamples,
+        return string.Format("I.47.23 sqrt(gamma*pr/rho) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -70,5 +70,5 @@
       if (noiseRatio != null) {
         var c_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * c.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * c.StandardDeviationPop();
         c_noise.AddRange(c.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(c);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman5.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman5.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman5.cs	(revision 17805)
@@ -28,6 +28,6 @@
     public override string Name {
       get {
-        return string.Format("I.9.18 G*m1*m2/((x2-x1)**2+(y2-y1)**2+(z2-z1)**2) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+        return string.Format("I.9.18 G*m1*m2/((x2-x1)**2+(y2-y1)**2+(z2-z1)**2) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -85,5 +85,5 @@
       if (noiseRatio != null) {
         var F_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * F.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * F.StandardDeviationPop();
         F_noise.AddRange(F.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(F);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman50.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman50.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman50.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("I.48.2 m*c**2/sqrt(1-v**2/c**2) | {0} samples | {1}", trainingSamples,
+        return string.Format("I.48.2 m*c**2/sqrt(1-v**2/c**2) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -70,5 +70,5 @@
       if (noiseRatio != null) {
         var E_n_noise   = new List<double>();
-        var sigma_noise = (double) noiseRatio * E_n.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * E_n.StandardDeviationPop();
         E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(E_n);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman51.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman51.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman51.cs	(revision 17805)
@@ -28,6 +28,6 @@
     public override string Name {
       get {
-        return string.Format("I.50.26 x1*(cos(omega*t)+alpha*cos(omega*t)**2) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+        return string.Format("I.50.26 x1*(cos(omega*t)+alpha*cos(omega*t)**2) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -72,5 +72,5 @@
       if (noiseRatio != null) {
         var x_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * x.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * x.StandardDeviationPop();
         x_noise.AddRange(x.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(x);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman52.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman52.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman52.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("II.2.42 kappa*(T2-T1)*A/d | {0} samples | {1}", trainingSamples,
+        return string.Format("II.2.42 kappa*(T2-T1)*A/d | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -74,5 +74,5 @@
       if (noiseRatio != null) {
         var Pwr_noise   = new List<double>();
-        var sigma_noise = (double) noiseRatio * Pwr.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * Pwr.StandardDeviationPop();
         Pwr_noise.AddRange(Pwr.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(Pwr);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman53.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman53.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman53.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("II.3.24 Pwr/(4*pi*r**2) | {0} samples | {1}", trainingSamples,
+        return string.Format("II.3.24 Pwr/(4*pi*r**2) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -68,5 +68,5 @@
       if (noiseRatio != null) {
         var flux_noise  = new List<double>();
-        var sigma_noise = (double) noiseRatio * flux.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * flux.StandardDeviationPop();
         flux_noise.AddRange(flux.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(flux);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman54.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman54.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman54.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("II.4.23 q/(4*pi*epsilon*r) | {0} samples | {1}", trainingSamples,
+        return string.Format("II.4.23 q/(4*pi*epsilon*r) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -70,5 +70,5 @@
       if (noiseRatio != null) {
         var Volt_noise  = new List<double>();
-        var sigma_noise = (double) noiseRatio * Volt.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * Volt.StandardDeviationPop();
         Volt_noise.AddRange(Volt.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(Volt);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman55.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman55.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman55.cs	(revision 17805)
@@ -28,6 +28,6 @@
     public override string Name {
       get {
-        return string.Format("II.6.11 1/(4*pi*epsilon)*p_d*cos(theta)/r**2 | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+        return string.Format("II.6.11 1/(4*pi*epsilon)*p_d*cos(theta)/r**2 | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -72,5 +72,5 @@
       if (noiseRatio != null) {
         var Volt_noise  = new List<double>();
-        var sigma_noise = (double) noiseRatio * Volt.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * Volt.StandardDeviationPop();
         Volt_noise.AddRange(Volt.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(Volt);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman56.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman56.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman56.cs	(revision 17805)
@@ -28,6 +28,6 @@
     public override string Name {
       get {
-        return string.Format("II.6.15a 3/(4*pi*epsilon)*p_d*z/r**5*sqrt(x**2+y**2) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+        return string.Format("II.6.15a 3/(4*pi*epsilon)*p_d*z/r**5*sqrt(x**2+y**2) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -77,5 +77,5 @@
       if (noiseRatio != null) {
         var Ef_noise    = new List<double>();
-        var sigma_noise = (double) noiseRatio * Ef.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * Ef.StandardDeviationPop();
         Ef_noise.AddRange(Ef.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(Ef);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman57.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman57.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman57.cs	(revision 17805)
@@ -29,6 +29,6 @@
       get {
         return string.Format(
-          "II.6.15b 3/(4*pi*epsilon)*p_d/r**3*cos(theta)*sin(theta) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+          "II.6.15b 3/(4*pi*epsilon)*p_d/r**3*cos(theta)*sin(theta) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -73,5 +73,5 @@
       if (noiseRatio != null) {
         var Ef_noise    = new List<double>();
-        var sigma_noise = (double) noiseRatio * Ef.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * Ef.StandardDeviationPop();
         Ef_noise.AddRange(Ef.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(Ef);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman58.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman58.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman58.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("II.8.7 3/5*q**2/(4*pi*epsilon*d) | {0} samples | {1}", trainingSamples,
+        return string.Format("II.8.7 3/5*q**2/(4*pi*epsilon*d) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -70,5 +70,5 @@
       if (noiseRatio != null) {
         var E_n_noise   = new List<double>();
-        var sigma_noise = (double) noiseRatio * E_n.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * E_n.StandardDeviationPop();
         E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(E_n);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman59.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman59.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman59.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("II.8.31 epsilon*Ef**2/2 | {0} samples | {1}", trainingSamples,
+        return string.Format("II.8.31 epsilon*Ef**2/2 | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -68,5 +68,5 @@
       if (noiseRatio != null) {
         var E_den_noise = new List<double>();
-        var sigma_noise = (double) noiseRatio * E_den.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * E_den.StandardDeviationPop();
         E_den_noise.AddRange(E_den.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(E_den);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman6.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman6.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman6.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("I.10.7 m_0/sqrt(1-v**2/c**2) | {0} samples | {1}", trainingSamples,
+        return string.Format("I.10.7 m_0/sqrt(1-v**2/c**2) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -70,5 +70,5 @@
       if (noiseRatio != null) {
         var m_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * m.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * m.StandardDeviationPop();
         m_noise.AddRange(m.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(m);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman60.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman60.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman60.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("II.10.9 sigma_den/epsilon*1/(1+chi) | {0} samples | {1}", trainingSamples,
+        return string.Format("II.10.9 sigma_den/epsilon*1/(1+chi) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -70,5 +70,5 @@
       if (noiseRatio != null) {
         var Ef_noise    = new List<double>();
-        var sigma_noise = (double) noiseRatio * Ef.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * Ef.StandardDeviationPop();
         Ef_noise.AddRange(Ef.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(Ef);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman61.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman61.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman61.cs	(revision 17805)
@@ -28,6 +28,6 @@
     public override string Name {
       get {
-        return string.Format("II.11.3 q*Ef/(m*(omega_0**2-omega**2)) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+        return string.Format("II.11.3 q*Ef/(m*(omega_0**2-omega**2)) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -74,5 +74,5 @@
       if (noiseRatio != null) {
         var x_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * x.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * x.StandardDeviationPop();
         x_noise.AddRange(x.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(x);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman62.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman62.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman62.cs	(revision 17805)
@@ -28,6 +28,6 @@
     public override string Name {
       get {
-        return string.Format("II.11.17 n_0*(1 + p_d*Ef*cos(theta)/(kb*T)) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+        return string.Format("II.11.17 n_0*(1 + p_d*Ef*cos(theta)/(kb*T)) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -76,5 +76,5 @@
       if (noiseRatio != null) {
         var n_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * n.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * n.StandardDeviationPop();
         n_noise.AddRange(n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(n);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman63.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman63.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman63.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("II.11.20 n_rho*p_d**2*Ef/(3*kb*T) | {0} samples | {1}", trainingSamples,
+        return string.Format("II.11.20 n_rho*p_d**2*Ef/(3*kb*T) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -74,5 +74,5 @@
       if (noiseRatio != null) {
         var Pol_noise   = new List<double>();
-        var sigma_noise = (double) noiseRatio * Pol.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * Pol.StandardDeviationPop();
         Pol_noise.AddRange(Pol.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(Pol);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman64.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman64.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman64.cs	(revision 17805)
@@ -28,6 +28,6 @@
     public override string Name {
       get {
-        return string.Format("II.11.27 n*alpha/(1-(n*alpha/3))*epsilon*Ef | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+        return string.Format("II.11.27 n*alpha/(1-(n*alpha/3))*epsilon*Ef | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -72,5 +72,5 @@
       if (noiseRatio != null) {
         var Pol_noise   = new List<double>();
-        var sigma_noise = (double) noiseRatio * Pol.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * Pol.StandardDeviationPop();
         Pol_noise.AddRange(Pol.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(Pol);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman65.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman65.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman65.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("II.11.28 1+n*alpha/(1-(n*alpha/3)) | {0} samples | {1}", trainingSamples,
+        return string.Format("II.11.28 1+n*alpha/(1-(n*alpha/3)) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -68,5 +68,5 @@
       if (noiseRatio != null) {
         var theta_noise = new List<double>();
-        var sigma_noise = (double) noiseRatio * theta.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * theta.StandardDeviationPop();
         theta_noise.AddRange(theta.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(theta);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman66.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman66.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman66.cs	(revision 17805)
@@ -28,6 +28,6 @@
     public override string Name {
       get {
-        return string.Format("II.13.17 1/(4*pi*epsilon*c**2)*2*I/r | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+        return string.Format("II.13.17 1/(4*pi*epsilon*c**2)*2*I/r | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -72,5 +72,5 @@
       if (noiseRatio != null) {
         var B_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * B.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * B.StandardDeviationPop();
         B_noise.AddRange(B.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(B);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman67.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman67.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman67.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("II.13.23 rho_c_0/sqrt(1-v**2/c**2) | {0} samples | {1}", trainingSamples,
+        return string.Format("II.13.23 rho_c_0/sqrt(1-v**2/c**2) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -70,5 +70,5 @@
       if (noiseRatio != null) {
         var rho_c_noise = new List<double>();
-        var sigma_noise = (double) noiseRatio * rho_c.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * rho_c.StandardDeviationPop();
         rho_c_noise.AddRange(rho_c.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(rho_c);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman68.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman68.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman68.cs	(revision 17805)
@@ -28,6 +28,6 @@
     public override string Name {
       get {
-        return string.Format("II.13.34 rho_c_0*v/sqrt(1-v**2/c**2) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+        return string.Format("II.13.34 rho_c_0*v/sqrt(1-v**2/c**2) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -70,5 +70,5 @@
       if (noiseRatio != null) {
         var j_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * j.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * j.StandardDeviationPop();
         j_noise.AddRange(j.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(j);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman69.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman69.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman69.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("II.15.4 -mom*B*cos(theta) | {0} samples | {1}", trainingSamples,
+        return string.Format("II.15.4 -mom*B*cos(theta) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -70,5 +70,5 @@
       if (noiseRatio != null) {
         var E_n_noise   = new List<double>();
-        var sigma_noise = (double) noiseRatio * E_n.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * E_n.StandardDeviationPop();
         E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(E_n);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman7.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman7.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman7.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("I.11.19 x1*y1+x2*y2+x3*y3 | {0} samples | {1}", trainingSamples,
+        return string.Format("I.11.19 x1*y1+x2*y2+x3*y3 | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -76,5 +76,5 @@
       if (noiseRatio != null) {
         var A_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * A.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * A.StandardDeviationPop();
         A_noise.AddRange(A.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(A);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman70.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman70.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman70.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("II.15.5 -p_d*Ef*cos(theta) | {0} samples | {1}", trainingSamples,
+        return string.Format("II.15.5 -p_d*Ef*cos(theta) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -70,5 +70,5 @@
       if (noiseRatio != null) {
         var E_n_noise   = new List<double>();
-        var sigma_noise = (double) noiseRatio * E_n.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * E_n.StandardDeviationPop();
         E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(E_n);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman71.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman71.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman71.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("II.21.32 q/(4*pi*epsilon*r*(1-v/c)) | {0} samples | {1}", trainingSamples,
+        return string.Format("II.21.32 q/(4*pi*epsilon*r*(1-v/c)) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -74,5 +74,5 @@
       if (noiseRatio != null) {
         var Volt_noise  = new List<double>();
-        var sigma_noise = (double) noiseRatio * Volt.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * Volt.StandardDeviationPop();
         Volt_noise.AddRange(Volt.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(Volt);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman72.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman72.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman72.cs	(revision 17805)
@@ -28,6 +28,6 @@
     public override string Name {
       get {
-        return string.Format("II.24.17 sqrt(omega**2/c**2-pi**2/d**2) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+        return string.Format("II.24.17 sqrt(omega**2/c**2-pi**2/d**2) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -70,5 +70,5 @@
       if (noiseRatio != null) {
         var k_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * k.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * k.StandardDeviationPop();
         k_noise.AddRange(k.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(k);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman73.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman73.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman73.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("II.27.16 epsilon*c*Ef**2 | {0} samples | {1}", trainingSamples,
+        return string.Format("II.27.16 epsilon*c*Ef**2 | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -70,5 +70,5 @@
       if (noiseRatio != null) {
         var flux_noise  = new List<double>();
-        var sigma_noise = (double) noiseRatio * flux.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * flux.StandardDeviationPop();
         flux_noise.AddRange(flux.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(flux);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman74.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman74.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman74.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("II.27.18 epsilon*Ef**2 | {0} samples | {1}", trainingSamples,
+        return string.Format("II.27.18 epsilon*Ef**2 | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -68,5 +68,5 @@
       if (noiseRatio != null) {
         var E_den_noise = new List<double>();
-        var sigma_noise = (double) noiseRatio * E_den.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * E_den.StandardDeviationPop();
         E_den_noise.AddRange(E_den.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(E_den);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman75.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman75.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman75.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("II.34.2a q*v/(2*pi*r) | {0} samples | {1}", trainingSamples,
+        return string.Format("II.34.2a q*v/(2*pi*r) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -70,5 +70,5 @@
       if (noiseRatio != null) {
         var I_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * I.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * I.StandardDeviationPop();
         I_noise.AddRange(I.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(I);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman76.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman76.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman76.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("II.34.2 q*v*r/2 | {0} samples | {1}", trainingSamples,
+        return string.Format("II.34.2 q*v*r/2 | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -70,5 +70,5 @@
       if (noiseRatio != null) {
         var mom_noise   = new List<double>();
-        var sigma_noise = (double) noiseRatio * mom.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * mom.StandardDeviationPop();
         mom_noise.AddRange(mom.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(mom);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman77.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman77.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman77.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("II.34.11 g_*q*B/(2*m) | {0} samples | {1}", trainingSamples,
+        return string.Format("II.34.11 g_*q*B/(2*m) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -72,5 +72,5 @@
       if (noiseRatio != null) {
         var omega_noise = new List<double>();
-        var sigma_noise = (double) noiseRatio * omega.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * omega.StandardDeviationPop();
         omega_noise.AddRange(omega.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(omega);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman78.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman78.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman78.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("II.34.29a q*h/(4*pi*m) | {0} samples | {1}", trainingSamples,
+        return string.Format("II.34.29a q*h/(4*pi*m) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -70,5 +70,5 @@
       if (noiseRatio != null) {
         var mom_noise   = new List<double>();
-        var sigma_noise = (double) noiseRatio * mom.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * mom.StandardDeviationPop();
         mom_noise.AddRange(mom.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(mom);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman79.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman79.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman79.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("II.34.29b g_*mom*B*Jz/h | {0} samples | {1}", trainingSamples,
+        return string.Format("II.34.29b g_*mom*B*Jz/h | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -74,5 +74,5 @@
       if (noiseRatio != null) {
         var E_n_noise   = new List<double>();
-        var sigma_noise = (double) noiseRatio * E_n.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * E_n.StandardDeviationPop();
         E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(E_n);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman8.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman8.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman8.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("I.12.1 mu*Nn | {0} samples | {1}", trainingSamples,
+        return string.Format("I.12.1 mu*Nn | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -68,5 +68,5 @@
       if (noiseRatio != null) {
         var F_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * F.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * F.StandardDeviationPop();
         F_noise.AddRange(F.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(F);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman80.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman80.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman80.cs	(revision 17805)
@@ -28,6 +28,6 @@
     public override string Name {
       get {
-        return string.Format("II.35.18 n_0/(exp(mom*B/(kb*T))+exp(-mom*B/(kb*T))) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+        return string.Format("II.35.18 n_0/(exp(mom*B/(kb*T))+exp(-mom*B/(kb*T))) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -74,5 +74,5 @@
       if (noiseRatio != null) {
         var n_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * n.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * n.StandardDeviationPop();
         n_noise.AddRange(n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(n);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman81.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman81.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman81.cs	(revision 17805)
@@ -28,6 +28,6 @@
     public override string Name {
       get {
-        return string.Format("II.35.21 n_rho*mom*tanh(mom*B/(kb*T)) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+        return string.Format("II.35.21 n_rho*mom*tanh(mom*B/(kb*T)) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -74,5 +74,5 @@
       if (noiseRatio != null) {
         var M_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * M.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * M.StandardDeviationPop();
         M_noise.AddRange(M.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(M);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman82.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman82.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman82.cs	(revision 17805)
@@ -29,6 +29,6 @@
       get {
         return string.Format(
-          "II.36.38 mom*B/(kb*T)+(mom*alpha*M)/(epsilon*c**2*kb*T) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+          "II.36.38 mom*B/(kb*T)+(mom*alpha*M)/(epsilon*c**2*kb*T) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -84,5 +84,5 @@
       if (noiseRatio != null) {
         var f_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * f.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * f.StandardDeviationPop();
         f_noise.AddRange(f.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(f);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman83.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman83.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman83.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("II.37.1 mom*(1+chi)*B | {0} samples | {1}", trainingSamples,
+        return string.Format("II.37.1 mom*(1+chi)*B | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -70,5 +70,5 @@
       if (noiseRatio != null) {
         var E_n_noise   = new List<double>();
-        var sigma_noise = (double) noiseRatio * E_n.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * E_n.StandardDeviationPop();
         E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(E_n);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman84.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman84.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman84.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("II.38.3 Y*A*x/d | {0} samples | {1}", trainingSamples,
+        return string.Format("II.38.3 Y*A*x/d | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -72,5 +72,5 @@
       if (noiseRatio != null) {
         var F_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * F.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * F.StandardDeviationPop();
         F_noise.AddRange(F.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(F);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman85.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman85.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman85.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("II.38.14 Y/(2*(1+sigma)) | {0} samples | {1}", trainingSamples,
+        return string.Format("II.38.14 Y/(2*(1+sigma)) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -68,5 +68,5 @@
       if (noiseRatio != null) {
         var mu_S_noise  = new List<double>();
-        var sigma_noise = (double) noiseRatio * mu_S.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * mu_S.StandardDeviationPop();
         mu_S_noise.AddRange(mu_S.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(mu_S);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman86.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman86.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman86.cs	(revision 17805)
@@ -28,6 +28,6 @@
     public override string Name {
       get {
-        return string.Format("III.4.32 1/(exp(h*omega/(kb*T))-1) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+        return string.Format("III.4.32 1/(exp(h*omega/(kb*T))-1) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -72,5 +72,5 @@
       if (noiseRatio != null) {
         var n_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * n.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * n.StandardDeviationPop();
         n_noise.AddRange(n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(n);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman87.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman87.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman87.cs	(revision 17805)
@@ -29,6 +29,6 @@
       get {
         return string.Format(
-          "III.4.33 h*omega/(exp(h*omega/(kb*T))-1) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+          "III.4.33 h*omega/(exp(h*omega/(kb*T))-1) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -73,5 +73,5 @@
       if (noiseRatio != null) {
         var E_n_noise   = new List<double>();
-        var sigma_noise = (double) noiseRatio * E_n.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * E_n.StandardDeviationPop();
         E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(E_n);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman88.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman88.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman88.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("III.7.38 2*mom*B/h | {0} samples | {1}", trainingSamples,
+        return string.Format("III.7.38 2*mom*B/h | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -70,5 +70,5 @@
       if (noiseRatio != null) {
         var omega_noise = new List<double>();
-        var sigma_noise = (double) noiseRatio * omega.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * omega.StandardDeviationPop();
         omega_noise.AddRange(omega.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(omega);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman89.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman89.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman89.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("III.8.54 sin(E_n*t/h)**2 | {0} samples | {1}", trainingSamples,
+        return string.Format("III.8.54 sin(E_n*t/h)**2 | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -70,5 +70,5 @@
       if (noiseRatio != null) {
         var prob_noise  = new List<double>();
-        var sigma_noise = (double) noiseRatio * prob.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * prob.StandardDeviationPop();
         prob_noise.AddRange(prob.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(prob);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman9.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman9.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman9.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("I.12.2 q1*q2/(4*pi*epsilon*r**2) | {0} samples | {1}", trainingSamples,
+        return string.Format("I.12.2 q1*q2/(4*pi*epsilon*r**2) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -72,5 +72,5 @@
       if (noiseRatio != null) {
         var F_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * F.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * F.StandardDeviationPop();
         F_noise.AddRange(F.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(F);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman90.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman90.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman90.cs	(revision 17805)
@@ -29,6 +29,6 @@
       get {
         return string.Format(
-          "III.9.52 (p_d*Ef*t/h*sin((omega-omega_0)*t/2)**2/((omega-omega_0)*t/2)**2 | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+          "III.9.52 (p_d*Ef*t/h*sin((omega-omega_0)*t/2)**2/((omega-omega_0)*t/2)**2 | {0}",
+           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -81,5 +81,5 @@
       if (noiseRatio != null) {
         var prob_noise  = new List<double>();
-        var sigma_noise = (double) noiseRatio * prob.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * prob.StandardDeviationPop();
         prob_noise.AddRange(prob.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(prob);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman91.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman91.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman91.cs	(revision 17805)
@@ -28,6 +28,6 @@
     public override string Name {
       get {
-        return string.Format("III.10.19 mom*sqrt(Bx**2+By**2+Bz**2) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+        return string.Format("III.10.19 mom*sqrt(Bx**2+By**2+Bz**2) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -72,5 +72,5 @@
       if (noiseRatio != null) {
         var E_n_noise   = new List<double>();
-        var sigma_noise = (double) noiseRatio * E_n.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * E_n.StandardDeviationPop();
         E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(E_n);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman92.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman92.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman92.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("III.12.43 n*h | {0} samples | {1}", trainingSamples,
+        return string.Format("III.12.43 n*h | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -64,5 +64,5 @@
       if (noiseRatio != null) {
         var L_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * L.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * L.StandardDeviationPop();
         L_noise.AddRange(L.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(L);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman93.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman93.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman93.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("III.13.18 2*E_n*d**2*k/h | {0} samples | {1}", trainingSamples,
+        return string.Format("III.13.18 2*E_n*d**2*k/h | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -72,5 +72,5 @@
       if (noiseRatio != null) {
         var v_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * v.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * v.StandardDeviationPop();
         v_noise.AddRange(v.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(v);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman94.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman94.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman94.cs	(revision 17805)
@@ -28,6 +28,6 @@
     public override string Name {
       get {
-        return string.Format("III.14.14 I_0*(exp(q*Volt/(kb*T))-1) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+        return string.Format("III.14.14 I_0*(exp(q*Volt/(kb*T))-1) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -74,5 +74,5 @@
       if (noiseRatio != null) {
         var I_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * I.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * I.StandardDeviationPop();
         I_noise.AddRange(I.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(I);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman95.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman95.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman95.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("III.15.12 2*U*(1-cos(k*d)) | {0} samples | {1}", trainingSamples,
+        return string.Format("III.15.12 2*U*(1-cos(k*d)) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -70,5 +70,5 @@
       if (noiseRatio != null) {
         var E_n_noise   = new List<double>();
-        var sigma_noise = (double) noiseRatio * E_n.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * E_n.StandardDeviationPop();
         E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(E_n);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman96.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman96.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman96.cs	(revision 17805)
@@ -28,6 +28,6 @@
     public override string Name {
       get {
-        return string.Format("III.15.14 h**2/(2*E_n*d**2) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+        return string.Format("III.15.14 h**2/(2*E_n*d**2) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -70,5 +70,5 @@
       if (noiseRatio != null) {
         var m_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * m.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * m.StandardDeviationPop();
         m_noise.AddRange(m.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(m);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman97.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman97.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman97.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("III.15.27 2*pi*alpha/(n*d) | {0} samples | {1}", trainingSamples,
+        return string.Format("III.15.27 2*pi*alpha/(n*d) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -70,5 +70,5 @@
       if (noiseRatio != null) {
         var k_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * k.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * k.StandardDeviationPop();
         k_noise.AddRange(k.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(k);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman98.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman98.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman98.cs	(revision 17805)
@@ -28,5 +28,5 @@
     public override string Name {
       get {
-        return string.Format("III.17.37 beta*(1+alpha*cos(theta)) | {0} samples | {1}", trainingSamples,
+        return string.Format("III.17.37 beta*(1+alpha*cos(theta)) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -70,5 +70,5 @@
       if (noiseRatio != null) {
         var f_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * f.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * f.StandardDeviationPop();
         f_noise.AddRange(f.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(f);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman99.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman99.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/Feynman99.cs	(revision 17805)
@@ -29,6 +29,6 @@
       get {
         return string.Format(
-          "III.19.51 -m*q**4/(2*(4*pi*epsilon)**2*h**2)*(1/n**2) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+          "III.19.51 -m*q**4/(2*(4*pi*epsilon)**2*h**2)*(1/n**2) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -76,5 +76,5 @@
       if (noiseRatio != null) {
         var E_n_noise   = new List<double>();
-        var sigma_noise = (double) noiseRatio * E_n.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * E_n.StandardDeviationPop();
         E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(E_n);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus1.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus1.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus1.cs	(revision 17805)
@@ -29,6 +29,6 @@
       get {
         return string.Format(
-          "Rutherford scattering: (Z_1*Z_2*alpha*hbar*c/(4*E_n*sin(theta/2)**2))**2 | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+          "Rutherford scattering: (Z_1*Z_2*alpha*hbar*c/(4*E_n*sin(theta/2)**2))**2 | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -82,5 +82,5 @@
       if (noiseRatio != null) {
         var A_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * A.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * A.StandardDeviationPop();
         A_noise.AddRange(A.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(A);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus10.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus10.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus10.cs	(revision 17805)
@@ -28,6 +28,6 @@
     public override string Name {
       get {
-        return string.Format("Goldstein 3.74: 2*pi*d**(3/2)/sqrt(G*(m1+m2)) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+        return string.Format("Goldstein 3.74: 2*pi*d**(3/2)/sqrt(G*(m1+m2)) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -72,5 +72,5 @@
       if (noiseRatio != null) {
         var t_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * t.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * t.StandardDeviationPop();
         t_noise.AddRange(t.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(t);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus11.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus11.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus11.cs	(revision 17805)
@@ -29,6 +29,6 @@
       get {
         return string.Format(
-          "Goldstein 3.99: sqrt(1+2*epsilon**2*E_n*L**2/(m*(Z_1*Z_2*q**2)**2)) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+          "Goldstein 3.99: sqrt(1+2*epsilon**2*E_n*L**2/(m*(Z_1*Z_2*q**2)**2)) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -84,5 +84,5 @@
       if (noiseRatio != null) {
         var alpha_noise = new List<double>();
-        var sigma_noise = (double) noiseRatio * alpha.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * alpha.StandardDeviationPop();
         alpha_noise.AddRange(alpha.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(alpha);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus12.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus12.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus12.cs	(revision 17805)
@@ -29,6 +29,6 @@
       get {
         return string.Format(
-          "Goldstein 8.56: sqrt((p-q*A_vec)**2*c**2+m**2*c**4)+q*Volt | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+          "Goldstein 8.56: sqrt((p-q*A_vec)**2*c**2+m**2*c**4)+q*Volt | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -78,5 +78,5 @@
       if (noiseRatio != null) {
         var E_n_noise   = new List<double>();
-        var sigma_noise = (double) noiseRatio * E_n.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * E_n.StandardDeviationPop();
         E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(E_n);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus13.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus13.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus13.cs	(revision 17805)
@@ -29,6 +29,6 @@
       get {
         return string.Format(
-          "Goldstein 12.80: 1/(2*m)*(p**2+m**2*omega**2*x**2*(1+alpha*x/y)) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+          "Goldstein 12.80: 1/(2*m)*(p**2+m**2*omega**2*x**2*(1+alpha*x/y)) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -79,5 +79,5 @@
       if (noiseRatio != null) {
         var E_n_noise   = new List<double>();
-        var sigma_noise = (double) noiseRatio * E_n.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * E_n.StandardDeviationPop();
         E_n_noise.AddRange(E_n.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(E_n);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus14.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus14.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus14.cs	(revision 17805)
@@ -29,6 +29,6 @@
       get {
         return string.Format(
-          "Jackson 2.11: q/(4*pi*epsilon*y**2)*(4*pi*epsilon*Volt*d-q*d*y**3/(y**2-d**2)**2) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+          "Jackson 2.11: q/(4*pi*epsilon*y**2)*(4*pi*epsilon*Volt*d-q*d*y**3/(y**2-d**2)**2) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -77,5 +77,5 @@
       if (noiseRatio != null) {
         var F_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * F.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * F.StandardDeviationPop();
         F_noise.AddRange(F.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(F);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus15.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus15.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus15.cs	(revision 17805)
@@ -29,6 +29,6 @@
       get {
         return string.Format(
-          "Jackson 3.45: q/sqrt(r**2+d**2-2*r*d*cos(alpha)) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+          "Jackson 3.45: q/sqrt(r**2+d**2-2*r*d*cos(alpha)) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -74,5 +74,5 @@
       if (noiseRatio != null) {
         var Volt_noise  = new List<double>();
-        var sigma_noise = (double) noiseRatio * Volt.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * Volt.StandardDeviationPop();
         Volt_noise.AddRange(Volt.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(Volt);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus16.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus16.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus16.cs	(revision 17805)
@@ -29,6 +29,6 @@
       get {
         return string.Format(
-          "Jackson 4.60: Ef*cos(theta)*((alpha-1)/(alpha+2)*d**3/r**2-r) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+          "Jackson 4.60: Ef*cos(theta)*((alpha-1)/(alpha+2)*d**3/r**2-r) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -76,5 +76,5 @@
       if (noiseRatio != null) {
         var Volt_noise  = new List<double>();
-        var sigma_noise = (double) noiseRatio * Volt.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * Volt.StandardDeviationPop();
         Volt_noise.AddRange(Volt.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(Volt);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus17.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus17.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus17.cs	(revision 17805)
@@ -29,6 +29,6 @@
       get {
         return string.Format(
-          "Jackson 11.38: sqrt(1-v**2/c**2)*omega/(1+v/c*cos(theta)) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+          "Jackson 11.38: sqrt(1-v**2/c**2)*omega/(1+v/c*cos(theta)) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -74,5 +74,5 @@
       if (noiseRatio != null) {
         var omega_0_noise = new List<double>();
-        var sigma_noise   = (double) noiseRatio * omega_0.StandardDeviationPop();
+        var sigma_noise   = (double) Math.Sqrt(noiseRatio.Value) * omega_0.StandardDeviationPop();
         omega_0_noise.AddRange(omega_0.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(omega_0);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus18.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus18.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus18.cs	(revision 17805)
@@ -28,6 +28,6 @@
     public override string Name {
       get {
-        return string.Format("Weinberg 15.2.1: 3/(8*pi*G)*(c**2*k_f/r**2+H_G**2) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+        return string.Format("Weinberg 15.2.1: 3/(8*pi*G)*(c**2*k_f/r**2+H_G**2) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -74,5 +74,5 @@
       if (noiseRatio != null) {
         var rho_0_noise = new List<double>();
-        var sigma_noise = (double) noiseRatio * rho_0.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * rho_0.StandardDeviationPop();
         rho_0_noise.AddRange(rho_0.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(rho_0);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus19.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus19.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus19.cs	(revision 17805)
@@ -29,6 +29,6 @@
       get {
         return string.Format(
-          "Weinberg 15.2.2: -1/(8*pi*G)*(c**4*k_f/r**2 + c**2*H_G**2*(1-2*alpha)) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+          "Weinberg 15.2.2: -1/(8*pi*G)*(c**4*k_f/r**2 + c**2*H_G**2*(1-2*alpha)) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -78,5 +78,5 @@
       if (noiseRatio != null) {
         var pr_noise    = new List<double>();
-        var sigma_noise = (double) noiseRatio * pr.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * pr.StandardDeviationPop();
         pr_noise.AddRange(pr.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(pr);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus2.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus2.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus2.cs	(revision 17805)
@@ -28,6 +28,6 @@
     public override string Name {
       get {
-        return string.Format("Friedman Equation: sqrt(8*pi*G*rho/3-alpha*c**2/d**2) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+        return string.Format("Friedman Equation: sqrt(8*pi*G*rho/3-alpha*c**2/d**2) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -74,5 +74,5 @@
       if (noiseRatio != null) {
         var H_G_noise   = new List<double>();
-        var sigma_noise = (double) noiseRatio * H_G.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * H_G.StandardDeviationPop();
         H_G_noise.AddRange(H_G.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(H_G);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus20.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus20.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus20.cs	(revision 17805)
@@ -29,6 +29,6 @@
       get {
         return string.Format(
-          "Schwarz 13.132 (Klein-Nishina): pi*alpha**2*h**2/(m**2*c**2)*(omega_0/omega)**2*(omega_0/omega+omega/omega_0-sin(beta)**2) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+          "Schwarz 13.132 (Klein-Nishina): pi*alpha**2*h**2/(m**2*c**2)*(omega_0/omega)**2*(omega_0/omega+omega/omega_0-sin(beta)**2) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -83,5 +83,5 @@
       if (noiseRatio != null) {
         var A_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * A.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * A.StandardDeviationPop();
         A_noise.AddRange(A.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(A);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus3.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus3.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus3.cs	(revision 17805)
@@ -29,5 +29,5 @@
       get {
         return string.Format(
-          "Compton Scattering: E_n/(1+E_n/(m*c**2)*(1-cos(theta))) | {0} samples | {1}", trainingSamples,
+          "Compton Scattering: E_n/(1+E_n/(m*c**2)*(1-cos(theta))) | {0}",
           noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
@@ -73,5 +73,5 @@
       if (noiseRatio != null) {
         var K_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * K.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * K.StandardDeviationPop();
         K_noise.AddRange(K.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(K);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus4.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus4.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus4.cs	(revision 17805)
@@ -29,6 +29,6 @@
       get {
         return string.Format(
-          "Radiated gravitational wave power: -32/5*G**4/c**5*(m1*m2)**2*(m1+m2)/r**5 | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+          "Radiated gravitational wave power: -32/5*G**4/c**5*(m1*m2)**2*(m1+m2)/r**5 | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -76,5 +76,5 @@
       if (noiseRatio != null) {
         var Pwr_noise   = new List<double>();
-        var sigma_noise = (double) noiseRatio * Pwr.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * Pwr.StandardDeviationPop();
         Pwr_noise.AddRange(Pwr.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(Pwr);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus5.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus5.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus5.cs	(revision 17805)
@@ -29,6 +29,6 @@
       get {
         return string.Format(
-          "Relativistic aberation: arccos((cos(theta2)-v/c)/(1-v/c*cos(theta2))) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+          "Relativistic aberation: arccos((cos(theta2)-v/c)/(1-v/c*cos(theta2))) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -71,5 +71,5 @@
       if (noiseRatio != null) {
         var theta1_noise = new List<double>();
-        var sigma_noise  = (double) noiseRatio * theta1.StandardDeviationPop();
+        var sigma_noise  = (double) Math.Sqrt(noiseRatio.Value) * theta1.StandardDeviationPop();
         theta1_noise.AddRange(theta1.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(theta1);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus6.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus6.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus6.cs	(revision 17805)
@@ -29,6 +29,6 @@
       get {
         return string.Format(
-          "N-slit diffraction: I_0*(sin(alpha/2)*sin(n*delta/2)/(alpha/2*sin(delta/2)))**2 | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+          "N-slit diffraction: I_0*(sin(alpha/2)*sin(n*delta/2)/(alpha/2*sin(delta/2)))**2 | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -75,5 +75,5 @@
       if (noiseRatio != null) {
         var I_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * I.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * I.StandardDeviationPop();
         I_noise.AddRange(I.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(I);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus7.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus7.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus7.cs	(revision 17805)
@@ -28,6 +28,6 @@
     public override string Name {
       get {
-        return string.Format("Goldstein 3.16: sqrt(2/m*(E_n-U-L**2/(2*m*r**2))) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+        return string.Format("Goldstein 3.16: sqrt(2/m*(E_n-U-L**2/(2*m*r**2))) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -74,5 +74,5 @@
       if (noiseRatio != null) {
         var v_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * v.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * v.StandardDeviationPop();
         v_noise.AddRange(v.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(v);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus8.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus8.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus8.cs	(revision 17805)
@@ -29,6 +29,6 @@
       get {
         return string.Format(
-          "Goldstein 3.55: m*k_G/L**2*(1+sqrt(1+2*E_n*L**2/(m*k_G**2))*cos(theta1-theta2)) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+          "Goldstein 3.55: m*k_G/L**2*(1+sqrt(1+2*E_n*L**2/(m*k_G**2))*cos(theta1-theta2)) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -81,5 +81,5 @@
       if (noiseRatio != null) {
         var k_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * k.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * k.StandardDeviationPop();
         k_noise.AddRange(k.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(k);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus9.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus9.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanBonus9.cs	(revision 17805)
@@ -29,6 +29,6 @@
       get {
         return string.Format(
-          "Goldstein 3.64: d*(1-alpha**2)/(1+alpha*cos(theta1-theta2)) | {0} samples | {1}",
-          trainingSamples, noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
+          "Goldstein 3.64: d*(1-alpha**2)/(1+alpha*cos(theta1-theta2)) | {0}",
+          noiseRatio == null ? "no noise" : string.Format(System.Globalization.CultureInfo.InvariantCulture, "noise={0:g}",noiseRatio));
       }
     }
@@ -73,5 +73,5 @@
       if (noiseRatio != null) {
         var r_noise     = new List<double>();
-        var sigma_noise = (double) noiseRatio * r.StandardDeviationPop();
+        var sigma_noise = (double) Math.Sqrt(noiseRatio.Value) * r.StandardDeviationPop();
         r_noise.AddRange(r.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
         data.Remove(r);
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanLargeInstanceProvider.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanLargeInstanceProvider.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanLargeInstanceProvider.cs	(revision 17805)
@@ -35,5 +35,5 @@
 
 
-      var noiseRatio = new double?[] { null, 1, 10E-2, 10E-4 };
+      var noiseRatio = new double?[] { null, 0.1, 0.3, 1 };
 
       #region types
@@ -163,6 +163,6 @@
 
 
-      foreach (var n in noiseRatio) {
-        foreach (var type in descriptorTypes) {
+      foreach (var type in descriptorTypes) {
+        foreach (var n in noiseRatio) {
           descriptorList.Add((IDataDescriptor)Activator.CreateInstance(type, rand.Next(), 10000, 10000, n));
         }
Index: /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanSmallInstanceProvider.cs
===================================================================
--- /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanSmallInstanceProvider.cs	(revision 17804)
+++ /trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Feynman/FeynmanSmallInstanceProvider.cs	(revision 17805)
@@ -35,5 +35,5 @@
 
 
-      var noiseRatio = new double?[] { null, 1, 10E-2, 10E-4 };
+      var noiseRatio = new double?[] { null, 0.1, 0.3, 1 };
 
       #region types
@@ -163,6 +163,6 @@
 
 
-      foreach (var n in noiseRatio) {
-        foreach (var type in descriptorTypes) {
+      foreach (var type in descriptorTypes) {
+        foreach (var n in noiseRatio) {
           descriptorList.Add((IDataDescriptor)Activator.CreateInstance(type, rand.Next(), 100, 100, n));
         }
