Quant-BnB: A Scalable Branch-and-Bound Method for Optimal Decision Trees with Continuous Features. (arXiv:2206.11844v1 [cs.LG])

Web: http://arxiv.org/abs/2206.11844

Decision trees are one of the most useful and popular methods in the machine
learning toolbox. In this paper, we consider the problem of learning optimal
decision trees, a combinatorial optimization problem that is challenging to
solve at scale. A common approach in the literature is to use greedy
heuristics, which may not be optimal. Recently there has been significant
interest in learning optimal decision trees using various approaches (e.g.,
based on integer programming, dynamic programming) -- to achieve computational …

arxiv decision features lg scalable trees