BART with Targeted Smoothing: An analysis of patient-specific stillbirth risk

Understand

This article introduces BART with Targeted Smoothing, or tsBART, a new Bayesian tree-based model for nonparametric regression.

• The goal of tsBART is to introduce smoothness over a single target covariate t, while not necessarily requiring smoothness over other covariates x.
• TsBART is based on the Bayesian Additive Regression Trees (BART) model, an ensemble of regression trees.
• TsBART extends BART by parameterizing each tree's terminal nodes with smooth functions of t, rather than independent scalars.