BARMPy: Bayesian additive regression models Python package

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-validat...

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Bibliographic Details
Published inComputational statistics Vol. 40; no. 5; pp. 2807 - 2824
Main Author Van Boxel, Danielle
Format Journal Article
LanguageEnglish
Published Heidelberg Springer Nature B.V 01.06.2025
Subjects
Algorithms
Applied mathematics
Bayesian analysis
Decision trees
Documentation
Libraries
Machine learning
Markov analysis
Neural networks
Probability
Regression models
Software
Online AccessGet full text
ISSN0943-4062
1613-9658
DOI10.1007/s00180-024-01535-9

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Summary: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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ISSN:0943-4062
1613-9658
DOI:10.1007/s00180-024-01535-9