Benchmarking experiments for time series machine learning

This repo contains indications of how to reproduce experiments for published algorithms in the areas of time series machine learning, including classification, clustering, regression, forecasting,

We explain experiments in notebooks which are meant to show how results can be recreated. We would expect you to adapt the code to your local set up.

Algorithms used are implemented in the aeon-toolkit and/or scikit-learn.

Examples can make use of tsml-eval, a toolkit used to run experiments.

currently this requires the main branch of aeon, until version 1.3 is released. This can be installed directly

pip install git+https://github.com/aeon-toolkit/aeon.git@main