  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.
