9.11 SVM with Radial Kernels

image credit: Manin Bocss

• The advantage of using a kernel rather than simply enlarging feature space is computational, since it is only necessary to compute $\binom{n}{2}$ kernel functions.
• For radial kernels, the feature space is implicit and infinite dimensional, so we could not do the computations in such a space anyways.