Time Series Machine Learning with Aeon: Classification and Regression
Abstract
We present the classification and regression modules of aeon , a Python library for all machine learning tasks involving time series. aeon follows the scikit-learn API and is compatible with its utilities such as model selection and pipelines. The toolkit contains a wide range of algorithms, including the state-of-the-art and popular benchmarks for each time series learning task. We demonstrate how to use the aeon toolkit for these tasks and give an example of where these algorithms may be useful. More information and an introductory video of the toolkit modules are available on the demo webpage https://aeon-tutorials.github.io/ECML-Demo-2025/ .
Cite
Text
Middlehurst et al. "Time Series Machine Learning with Aeon: Classification and Regression." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2025. doi:10.1007/978-3-032-06129-4_26Markdown
[Middlehurst et al. "Time Series Machine Learning with Aeon: Classification and Regression." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2025.](https://mlanthology.org/ecmlpkdd/2025/middlehurst2025ecmlpkdd-time/) doi:10.1007/978-3-032-06129-4_26BibTeX
@inproceedings{middlehurst2025ecmlpkdd-time,
title = {{Time Series Machine Learning with Aeon: Classification and Regression}},
author = {Middlehurst, Matthew and Bagnall, Anthony J. and Forestier, Germain and Ismail-Fawaz, Ali and Guillaume, Antoine},
booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
year = {2025},
pages = {432-437},
doi = {10.1007/978-3-032-06129-4_26},
url = {https://mlanthology.org/ecmlpkdd/2025/middlehurst2025ecmlpkdd-time/}
}