Not very important and for a learning project I find using cvxpy a better idea as it's more readable ( like you did ) but:
Solving the full quadratic optimization problem for SVMs in basically impossible to do. You are forming an n^2 matrix, so I'm going to let you imagine what happens when n = 100 000.
Using people use either approximation methods ( Incomplete Cholesky, Nystrom ) or do it exactly but iteratively ( SMO, Pegasos... )
I'm implementing them for class right now so it's still fresh in my head haha
Solving the full quadratic optimization problem for SVMs in basically impossible to do. You are forming an n^2 matrix, so I'm going to let you imagine what happens when n = 100 000.
Using people use either approximation methods ( Incomplete Cholesky, Nystrom ) or do it exactly but iteratively ( SMO, Pegasos... )
I'm implementing them for class right now so it's still fresh in my head haha