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Activity Number: 20 - Bayesian Additive Regression Trees: Making an Impact
Type: Topic Contributed
Date/Time: Sunday, July 28, 2019 : 2:00 PM to 3:50 PM
Sponsor: International Society for Bayesian Analysis (ISBA)
Abstract #306923 Presentation
Title: XBART: Accelerated Bayesian Additive Regression Trees
Author(s): P. Richard Hahn* and Jingyu He
Companies: Arizona State University and Chicago Booth
Keywords: BART; regression trees; computation; algorithm

In this talk, I will describe a modified version of BART that is amenable to fast posterior estimation. We present a fitting algorithm that matches the remarkable predictive accuracy of previous BART implementations, but is orders of magnitude faster and uses a fraction of the memory. Simulation studies show that the new method is comparable in computation time and more accurate at function estimation than both random forests and gradient boosting.

Authors who are presenting talks have a * after their name.

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