Description Usage Arguments Details Value Author(s) See Also Examples
Calculates the polynomial 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  polykernel(X, d, Y = NULL)

X 
matrix containing a data point in each column 
d 
polynomial kernel degree 
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 polynomial kernel, which is defined as
k(x, y) = (<x, y> + 1)^d
where x, y are data points and d is the polynomial kernel degree.
polynomial kernel matrix K
for the given dataset
Jan Saputra Mueller
1 2 3  ## generate sinc data and calculate polynomial kernel matrix with d = 5
d < sincdata(100, noise = 0.1)
K < polykernel(d$X, 5)

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