Some commonly used kernels

Polynomial:

Parameters that the user must choose

Gaussian radial basis function

Neural net:

For the neural network kernel, there is one “hidden unit” per support vector, so the process of fitting the maximum margin hyperplane decides how many hidden units to use. Also, it may violate Mercer’s condition.