Tslearn, a Machine Learning Toolkit for Time Series Data
Abstract
tslearn is a general-purpose Python machine learning library for time series that offers tools for pre-processing and feature extraction as well as dedicated models for clustering, classification and regression. It follows scikit-learn's Application Programming Interface for transformers and estimators, allowing the use of standard pipelines and model selection tools on top of tslearn objects. It is distributed under the BSD-2-Clause license, and its source code is available at https://github.com/tslearn-team/tslearn.
Cite
Text
Tavenard et al. "Tslearn, a Machine Learning Toolkit for Time Series Data." Machine Learning Open Source Software, 2020.Markdown
[Tavenard et al. "Tslearn, a Machine Learning Toolkit for Time Series Data." Machine Learning Open Source Software, 2020.](https://mlanthology.org/mloss/2020/tavenard2020jmlr-tslearn/)BibTeX
@article{tavenard2020jmlr-tslearn,
title = {{Tslearn, a Machine Learning Toolkit for Time Series Data}},
author = {Tavenard, Romain and Faouzi, Johann and Vandewiele, Gilles and Divo, Felix and Androz, Guillaume and Holtz, Chester and Payne, Marie and Yurchak, Roman and Rußwurm, Marc and Kolar, Kushal and Woods, Eli},
journal = {Machine Learning Open Source Software},
year = {2020},
pages = {1-6},
volume = {21},
url = {https://mlanthology.org/mloss/2020/tavenard2020jmlr-tslearn/}
}