bartMachine: Machine Learning with Bayesian Additive Regression Trees
Year: 2016
Type: article
Abstract: We present a new package in R implementing Bayesian additive regression trees (BART). The package introduces many new features for data analysis using BART such as variable selection, interaction detection, model diagnostic plots, incorporation of missing data and the ability to save trees for future prediction. It is significantly faster than the current R implementation, parallelized, and capable of handling both large sample sizes and high-dimensional data.
Source: Journal of Statistical Software
Authors: Adam Kapelner, Justin Bleich
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W2327770667