BARMPy：贝叶斯加性回归模型 Python 软件包

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2024-08-04 DOI:10.1007/s00180-024-01535-9

Danielle Van Boxel

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引用次数: 0

摘要

我们将贝叶斯加性回归网络（BARN）作为一个 Python 软件包（barmpy）提供给广大机器学习从业者，其文档请访问 https://dvbuntu.github.io/barmpy/。我们面向对象的设计与 SciKit-Learn 兼容，允许使用交叉验证等工具。为了方便学习使用 barmpy，我们编写了配套教程，对文档中的参考信息进行了扩展。任何感兴趣的用户都可以从官方 PyPi 代码库中 pip 安装 barmpy。barmpy 还是通用贝叶斯加法回归模型的 Python 基线库。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

BARMPy: Bayesian additive regression models Python package

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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-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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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.