Tslearn, A Machine Learning Toolkit for Time Series Data

Tslearn, A Machine Learning Toolkit for Time Series Data. Tavenard, R., Faouzi, J., Vandewiele, G., Divo, F., Androz, G., Holtz, C., Payne, M., Yurchak, R., Rußwurm, M., Kolar, K., & Woods, E. Journal of Machine Learning Research, 21(118):1–6, 2020.

Paper abstract bibtex

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.

@article{tavenard_tslearn_2020,
	title = {Tslearn, {A} {Machine} {Learning} {Toolkit} for {Time} {Series} {Data}},
	volume = {21},
	issn = {1533-7928},
	url = {http://jmlr.org/papers/v21/20-091.html},
	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.},
	number = {118},
	urldate = {2021-08-27},
	journal = {Journal of Machine Learning Research},
	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},
	year = {2020},
	pages = {1--6},
}

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