Support vector machine

Support vector machine: A model learning a boundary by maximising margin, optionally using kernels for nonlinear relationships. Support vectors determine the solution. Scaling and regularisation matter; complex kernels increase computational cost. This perspective connects the definition with practical behaviour in artificial intelligence systems.