diff --git a/19_nystroem_approximation_code.R b/19_nystroem_approximation_code.R
index 49b8aac..b289f03 100644
--- a/19_nystroem_approximation_code.R
+++ b/19_nystroem_approximation_code.R
@@ -1,6 +1,6 @@
 # compute the gaussian kernel between each row of X1 and each row of X2
 # should be done more efficiently
-gausskernel <-
+gausskernel.nakr <-
 function(X1, X2, sigma2)
 {
   n1 <- dim(X1)[1]
@@ -34,7 +34,7 @@ function(X, y, sigma2=NULL, lambda=1E-4, landmarks=NULL, nb.landmarks=NULL)
   X <- scale(X)
   y <- scale(y)
 
-  C <- gausskernel(X, as.matrix(X[splidx,]), sigma2)
+  C <- gausskernel.nakr(X, as.matrix(X[splidx,]), sigma2)
   K11 <- C[splidx,]
 
   svdK11 <- svd(K11)
@@ -80,7 +80,7 @@ function(o, newdata)
   }
   newdata <- scale(newdata,center=attr(o$X,"scaled:center"),
                    scale=attr(o$X,"scaled:scale"))
-  Ktest <- gausskernel(newdata, as.matrix(o$X[o$splidx,]), o$sigma2)
+  Ktest <- gausskernel.nakr(newdata, as.matrix(o$X[o$splidx,]), o$sigma2)
   yh <- Ktest %*% o$beta
   yh <- (yh * attr(o$y,"scaled:scale")) + attr(o$y,"scaled:center")
 }