I have a question regarding machine learning and specifically kernel functions. Suppose we have a Kernel function, say K(x), and also another distinct one, say K'(x). I want to know is K(K'(x)) a kernel function as well? That is, if one feeds the output of a kernel function to another kernel, what does it mean? does it make sense or not? Another question is about the expected behavior of linear combination of well-known kernels,such as RBF, polynomial and MLP. Suppose the MLP kernel yields 60% of accuracy in a classification task and RBF yields 85%. Does necessarily the RBF+MLP yield a better accuracy compared to the one resulted by MLP? Thanks in advance.
I'm voting to close this question as off-topic because it is a mathematics question and not a programming question. It has also been posted here.