B.2All Subsets Kernel

We define the feature again as the product of powers of input attributes. However, in this case, the choice of power is restricted to [0,1], i.e. the feature is present or absent. For_n_input dimensions (number of attributes) we have2_n_possible combinations.

Let’s compute the kernel function:

(B.6)

where the last identity follows from the fact that,

(B.7) i.e. a sum over all possible combinations. Note that in this case again, it is much efficient to compute the kernel directly than to sum over the features. Also note that in this case there is no decaying factor multiplying the monomials.

B.3. THEGAUSSIANKERNEL79