aeon is a unified Python 3 library for all machine learning tasks involving time series. The package contains modules for time series forecasting, classification, extrinsic regression and clustering, as well as a variety of utilities, transformations and distance measures designed for time series data. aeon also has a number of experimental modules for tasks such as anomaly detection, similarity search and segmentation. aeon follows the scikit-learn API as much as possible to help new users and enable easy integration of aeon estimators with useful tools such as model selection and pipelines. It provides a broad library of time series algorithms, including efficient implementations of the very latest advances in research. Using a system of optional dependencies, aeon integrates a wide variety of packages into a single interface while keeping the core framework with minimal dependencies. The package is distributed under the 3-Clause BSD license and is available at https://github.com/ aeon-toolkit/aeon. This version was submitted to the JMLR journal on 02 Nov 2023 for v0.5.0 of aeon. At the time of this preprint aeon has released v0.9.0, and has had substantial changes.

翻译：aeon是一个统一的Python 3库，适用于所有涉及时间序列的机器学习任务。该软件包包含用于时间序列预测、分类、外生回归和聚类的模块，以及一系列专为时间序列数据设计的实用工具、变换方法和距离度量。aeon还包含多个实验性模块，用于异常检测、相似性搜索和分割等任务。aeon尽可能遵循scikit-learn API，以帮助新用户并实现aeon估计器与模型选择和流水线等实用工具的轻松集成。它提供了一个广泛的时间序列算法库，包括最新研究成果的高效实现。通过可选的依赖项系统，aeon将多种软件包集成到单一接口中，同时保持核心框架的依赖项最小化。该软件包在3-Clause BSD许可证下分发，可在https://github.com/aeon-toolkit/aeon获取。此版本于2023年11月2日提交至JMLR期刊，对应aeon的v0.5.0版本。在本预印本发布时，aeon已发布v0.9.0版本，并进行了重大更新。