Making Tree Ensembles Interpretable: A Bayesian Model Selection Approach

Satoshi Hara, Kohei Hayashi

Abstract: Tree ensembles, such as random forests, are renowned for their high prediction performance. However, their interpretability is critically limited due to the enormous complexity. In this study, we p...