Seglearn: A Python Package for Learning Sequences and Time Series
Machine Learning
2019-01-28 v3 Machine Learning
Abstract
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
Cite
@article{arxiv.1803.08118,
title = {Seglearn: A Python Package for Learning Sequences and Time Series},
author = {David M. Burns and Cari M. Whyne},
journal= {arXiv preprint arXiv:1803.08118},
year = {2019}
}