Calculates the RBF kernel matrix for the dataset contained in the matrix X
,
where each row of X
is a data point. If Y
is also a matrix (with the
same number of columns as X
), the kernel function is evaluated between all
data points of X
and Y
.
1 
X 
matrix containing a data point in each row 
sigma 
kernel width of rbf kernel 
Y 
leave this NULL if the kernel function should be evaluated between the data points only contained in

Each row of X
must be a data point, i.e. X = (x_1, x_2, ..., x_n).
The kernel matrix K
is then defined as
K = (k(x_i, x_j)), i,j=1,...,n
If Y
is not NULL and also contains data points in each row, i.e. Y = (y_1, y_2, ..., y_m),
the kernel matrix K
of X
and Y
is defined as
K = (k(x_i, x_j)), i=1,...,n, j=1,...,m
In this case, k is the rbf (radial basis function) kernel, which is defined as
k(x, y) = exp(0.5*\\x  y\\\^2/sigma)
where x, y are data points and sigma is the rbf kernel width.
RBF kernel matrix K
for the given dataset
Jan Saputra Mueller
1 2 3 
Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.
Please suggest features or report bugs with the GitHub issue tracker.
All documentation is copyright its authors; we didn't write any of that.