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
this https URL 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.

aeon 是一个用于时间序列的机器学习任务的统一 Python 3 库，包括时间序列预测、分类、外部回归、聚类等模块，以及用于时间序列数据的各种实用工具、转换和距离度量。它还有一些用于异常检测、相似性搜索和分割等任务的实验模块，遵循尽可能与 scikit-learn API 兼容的设计，使得新用户容易使用并能够轻松将 aeon 估计器与模型选择和管道等有用工具集成。它提供了一个广泛的时间序列算法库，包括最新研究进展的高效实现。aeon 通过可选依赖的系统将各种包集成到一个单一接口中，并保持核心框架的最小依赖。该软件包在 3-Clause BSD 许可下发布，在此 https URL aeon-toolkit/aeon 可获得。该版本于 2023 年 11 月 2 日提交给 JMLR 期刊，适用于 aeon 的 v0.5.0。在此预印本编写时，aeon 已发布 v0.9.0，并且进行了重大更改。