Nonparametric Machine Learning and Efficient Computation with Bayesian Additive Regression Trees: The BART R Package

Nonparametric Machine Learning and Efficient Computation with Bayesian Additive Regression Trees: The BART R Package

In this article, we introduce the BART R package which is an acronym for Bayesian additive regression trees. BART is a Bayesian nonparametric, machine learning, ensemble predictive modeling method for continuous, binary, categorical and time-to-event outcomes. Furthermore, BART is a tree-based, blac...

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Bibliographic Details
Main Authors: Rodney Sparapani, Charles Spanbauer, Robert McCulloch
Format: Article
Language:English
Published: Foundation for Open Access Statistics 2021-01-01
Series:Journal of Statistical Software
Subjects:
binary trees
black-box
categorical
competing risks
continuous
ensemble predictive model
Online Access:https://www.jstatsoft.org/index.php/jss/article/view/3668

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https://www.jstatsoft.org/index.php/jss/article/view/3668

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