{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/barmpy-bayesian-additive-regression-models","title":"BARMPy: Bayesian Additive Regression Models Python Package","arxiv_id":"2404.04738","date":"2024-04-06","proceeding":null,"authors":["Danielle Van Boxel"],"abstract":"We make Bayesian Additive Regression Networks (BARN) available as a Python package, \\texttt{barmpy}, with documentation at \\url{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 \\texttt{barmpy}, we produce a companion tutorial that expands on reference information in the documentation. Any interested user can \\texttt{pip install barmpy} from the official PyPi repository. \\texttt{barmpy} also serves as a baseline Python library for generic Bayesian Additive Regression Models.","url_abs":"https://arxiv.org/abs/2404.04738v1","url_pdf":"https://arxiv.org/pdf/2404.04738v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"barmpy-bayesian-additive-regression-models","repo_url":"https://github.com/dvbuntu/barmpy","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"regression-1","task_name":"regression"}],"methods":[{"method_slug":null,"method_name":"Library"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}