PyAutoFit：一种用于模型合成与拟合的类概率程序设计语言
PyAutoFit: A Classy Probabilistic Programming Language for Model Composition and Fitting
摘要：
学术界和数据科学的一个主要趋势是快速采用贝叶斯统计进行数据分析和建模，从而导致概率编程语言（PPL）的发展。PPL提供了一个框架，允许用户轻松地指定概率模型并自动执行推理。PyAutoFit是一个基于Python的PPL，它与建模的所有方面（例如，模型、数据、拟合过程、可视化、结果），并因此提供建模的每个方面的完整管理。这包括从各个模型组件组成高维模型，自定义拟合过程以及在模型拟合之前执行数据增强。高级功能包括用于分析大型建模结果套件的数据库工具，以及通过非线性搜索链接利用问题的特定领域知识。PyAutoFit附带的是autofit工作区（请参阅https：//github.com/Jammy2211/autofit_workspace），其中包括示例脚本和HowToFit系列讲座，该讲座向非专家介绍模型拟合，并提供如何使用PyAutoFit开始项目的指南。读者现在就可以尝试PyAutoFit，可以去Binder上的Introduction Notebook（参见https：//mybinder.org/v2/gh/Jammy2211/autofit_workspace/HEAD）或查看我们的readthedocs（参见https：//pyautofit.readthedocs.io/en/latest/）以获得PyAutoFit功能的完整概述。
英文摘要：
A major trend in academia and data science is the rapid adoption of Bayesian statistics for data analysis and modeling, leading to the development of probabilistic programming languages (PPL). A PPL provides a framework that allows users to easily specify a probabilistic model and perform inference automatically. PyAutoFit is a Python-based PPL which interfaces with all aspects of the modeling (e.g., the model, data, fitting procedure, visualization, results) and therefore provides complete management of every aspect of modeling. This includes composing high-dimensionality models from individual model components, customizing the fitting procedure and performing data augmentation before a model-fit. Advanced features include database tools for analysing large suites of modeling results and exploiting domain-specific knowledge of a problem via non-linear search chaining. Accompanying PyAutoFit is the autofit workspace (see https://github.com/Jammy2211/autofit_workspace), which includes example scripts and the HowToFit lecture series which introduces non-experts to model-fitting and provides a guide on how to begin a project using PyAutoFit. Readers can try PyAutoFit right now by going to the introduction Jupyter notebook on Binder (see https://mybinder.org/v2/gh/Jammy2211/autofit_workspace/HEAD) or checkout our readthedocs(see https://pyautofit.readthedocs.io/en/latest/) for a complete overview of PyAutoFit's features.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
