Skip to Main content Skip to Navigation
Journal articles

pyts: A Python Package for Time Series Classification

Johann Faouzi 1, 2 Hicham Janati 3, 4
2 ARAMIS - Algorithms, models and methods for images and signals of the human brain
SU - Sorbonne Université, Inria de Paris, ICM - Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute
4 PARIETAL - Modelling brain structure, function and variability based on high-field MRI data
Inria Saclay - Ile de France, NEUROSPIN - Service NEUROSPIN
Abstract : pyts is an open-source Python package for time series classification. This versatile toolbox provides implementations of many algorithms published in the literature, preprocessing functionalities, and data set loading utilities. pyts relies on the standard scientific Python packages numpy, scipy, scikit-learn, joblib, and numba, and is distributed under the BSD-3-Clause license. Documentation contains installation instructions, a detailed user guide, a full API description, and concrete self-contained examples. Source code and documentation can be downloaded from https://github.com/johannfaouzi/pyts.
Document type :
Journal articles
Complete list of metadatas

Cited literature [16 references]  Display  Hide  Download

https://hal.inria.fr/hal-02883389
Contributor : Johann Faouzi <>
Submitted on : Monday, June 29, 2020 - 9:58:02 AM
Last modification on : Wednesday, July 1, 2020 - 3:21:31 AM

File

19-763.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-02883389, version 1

Citation

Johann Faouzi, Hicham Janati. pyts: A Python Package for Time Series Classification. Journal of Machine Learning Research, Microtome Publishing, 2020, 21, pp.1 - 6. ⟨hal-02883389⟩

Share

Metrics

Record views

29

Files downloads

42