Seglearn: A Python Package for Learning Sequences and Time Series. Seglearn is an open-source python package for machine learning time series or sequences using a sliding window segmentation approach. The implementation provides a flexible pipeline for tackling classification, regression, and forecasting problems with multivariate sequence and contextual data. This package is compatible with scikit-learn and is listed under scikit-learn Related Projects. The package depends on numpy, scipy, and scikit-learn. Seglearn is distributed under the BSD 3-Clause License. Documentation includes a detailed API description, user guide, and examples. Unit tests provide a high degree of code coverage.
Keywords for this software
References in zbMATH (referenced in 6 articles , 2 standard articles )
Showing results 1 to 6 of 6.
- Julien Siebert, Janek Groß, Christof Schroth: A systematic review of Python packages for time series analysis (2021) arXiv
- Faouzi, Johann; Janati, Hicham: pyts: a Python package for time series classification (2020)
- Mathew Schwartz; Todd C. Pataky; Cyril J. Donnelly: seg1d: A Python package for Automated segmentation of one-dimensional (1D) data (2020) not zbMATH
- Tavenard, Romain; Faouzi, Johann; Vandewiele, Gilles; Divo, Felix; Androz, Guillaume; Holtz, Chester; Payne, Marie; Yurchak, Roman; Rußwurm, Marc; Kolar, Kushal; Woods, Eli: tslearn, a machine learning toolkit for time series data (2020)
- Burns, David M.; Whyne, Cari M.: Seglearn: a Python package for learning sequences and time series (2018)
- David M. Burns, Cari M. Whyne: Seglearn: A Python Package for Learning Sequences and Time Series (2018) arXiv