Computational Statistics
BARMPy: Bayesian additive regression models Python package
Danielle Van Boxel
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Publication type: Journal Article
Publication date: 2024-08-04
Journal:
Computational Statistics
scimago Q2
SJR: 0.566
CiteScore: 2.9
Impact factor: 1
ISSN: 09434062, 16139658
Abstract
We make Bayesian additive regression networks (BARN) available as a Python package, barmpy, with documentation at https://dvbuntu.github.io/barmpy/ for general machine learning practitioners. Our object-oriented design is compatible with SciKit-Learn, allowing usage of their tools like cross-validation. To ease learning to use barmpy, we produce a companion tutorial that expands on reference information in the documentation. Any interested user can pip install barmpy from the official PyPi repository. barmpy also serves as a baseline Python library for generic Bayesian additive regression models.
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