Tim Coleman

Asymptotic Distributions and Rates of Convergence for Random Forests via Generalized U-statistics

2019 · arXiv (Cornell University)

Random forests remain among the most popular off-the-shelf supervised learning algorithms. Despite their well-documented empirical success, however, until recently, few theoretical results were available to describe their performance and behavior. In this work we push …