Optimal classification trees

Classification and regression trees have been traditionally grown by recursive partitioning, i.e. by a top-down search for “locally optimal” splits. The “local”, or “one-step”, optimization of splits can to some extent, using the present power of computer hardware, be substituted by the full optimization of whole trees. In this paper, two bottom-up optimization algorithms are outlined and first experimental experience is presented.