“CORELS (Certifiable Optimal RulE ListS) is a custom discrete optimization technique for building rule lists over a categorical feature space. Our algorithm provides the optimal solution, with a certificate of optimality. By leveraging algorithmic bounds, efficient data structures, and computational reuse, we achieve several orders of magnitude speedup in time and a massive reduction of memory consumption. Our approach produces optimal rule lists on practical problems in seconds. This framework is a novel alternative to CART and other decision tree methods.”