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A Mixing Time Lower Bound for a Simplified Version of BART. (arXiv:2210.09352v1 [stat.ML])
Oct. 19, 2022, 1:13 a.m. | Omer Ronen, Theo Saarinen, Yan Shuo Tan, James Duncan, Bin Yu
stat.ML updates on arXiv.org arxiv.org
Bayesian Additive Regression Trees (BART) is a popular Bayesian
non-parametric regression algorithm. The posterior is a distribution over sums
of decision trees, and predictions are made by averaging approximate samples
from the posterior.
The combination of strong predictive performance and the ability to provide
uncertainty measures has led BART to be commonly used in the social sciences,
biostatistics, and causal inference.
BART uses Markov Chain Monte Carlo (MCMC) to obtain approximate posterior
samples over a parameterized space of sums of …
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