BARMPy: Bayesian additive regression models Python']Python package

被引:0
|
作者
Van Boxel, Danielle [1 ,2 ]
机构
[1] Univ Arizona, Appl Math GIDP, Tucson, AZ 85721 USA
[2] Univ Arizona, Data Divers Lab, Tucson, AZ 85721 USA
关键词
Machine learning; !text type='Python']Python[!/text; MCMC; Software; MARKOV-CHAIN;
D O I
10.1007/s00180-024-01535-9
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
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.
引用
收藏
页数:18
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