bartmachine: machine learning with bayesian additive regression trees

Clicks: 316
ID: 193992
2016
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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.
Reference Key
kapelner2016journalbartmachine: Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Adam Kapelner;Justin Bleich
Journal open geospatial data, software and standards
Year 2016
DOI
10.18637/jss.v070.i04
URL
https://www.jstatsoft.org/index.php/jss/article/view/2617
Keywords
statistics Machine learning r bayesian statistical learning

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