Highly Influenced

@article{Hernndez2018BayesianAR, title={Bayesian Additive Regression Trees using Bayesian model averaging}, author={Belinda Hern{\'a}ndez and Adrian E. Raftery and Stephen R Pennington and Andrew C. Parnell}, journal={Statistics and Computing}, year={2018}, volume={28}, pages={869-890} }

- Published 2018 in Statistics and Computing
DOI:10.1007/s11222-017-9767-1

Bayesian Additive Regression Trees (BART) is a statistical sum of trees model. It can be considered a Bayesian version of machine learning tree ensemble methods where the individual trees are the base learners. However for datasets where the number of variables p is large (e.g. p > 5, 000) the algorithm can become prohibitively expensive, computationally. Another method which is popular for high dimensional data is random forests, a machine learning algorithm which grows trees using a greedy… CONTINUE READING