Authors: | Adam Kapelner, Justin Bleich | ||||||
Title: | bartMachine: Machine Learning with Bayesian Additive Regression Trees | ||||||
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. | ||||||
Page views:: 5055. Submitted: 2013-12-31. Published: 2016-04-04. |
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Paper: |
bartMachine: Machine Learning with Bayesian Additive Regression Trees
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DOI: |
10.18637/jss.v070.i04
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![]() This work is licensed under the licenses Paper: Creative Commons Attribution 3.0 Unported License Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license. |