This is a purely hypothetical question and doesn't relate to any specific application.
Suppose you have two separate linear boundaries that can divide a bunch of data points into either categories A and B, or categories C and D. Is there a standard way of measuring their degree of "similarity" such as looking at the angle between them, computing the dot product etc.
I am wondering if such a metric exists for non-linear boundaries as well. Assuming of course that the classifiers are of the same type (e.g. both SVM).