Hi Shishir.
The algorithms are identical. However the direction of the eigenvectors
that generate the new coordinates
are only defined up to the sign. So the sign of the axis in both PCA and
KPCA is detemined by the details of the algorithm
computing the eigenvector. I is not really surprising if
Hi
Just wanted to know what is the difference between PCA and KPCA with
linear kernel. They produce the same result on columns 1, 2, etc. But,
the values in column 0 of the fitted transform of one is negative of
other. Shouldn't they both be the same?
--
sp
