Popular loss functions include the hinge loss (for linear SVMs) and the log loss (for linear logistic regression). If the regularization function is convex, then the above is a convex problem. Many algorithms exist for solving such problems; popular ones for linear classification include (stochastic) gradient descent, L-BFGS, coordinate descent and Newton methods.
Popular loss functions include the hinge loss (for linear SVMs) and the log loss (for linear logistic regression). If the regularization function is convex then the above is a convex problem. Many algorithms exist for solving such problems; popular ones for linear classification include (stochastic) gradient descent, L-BFGS, coordinate descent and Newton methods.