|
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
|
|
Abstract:
|
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.
