Seglearn: A Python Package for Learning Sequences and Time Series
This is an incremental contribution, offering a new tool for researchers and practitioners working with sequence and time series data in Python.
The authors introduced Seglearn, an open-source Python package for machine learning on time series and sequences using a sliding window segmentation approach, providing a flexible pipeline compatible with scikit-learn for classification, regression, and forecasting tasks.
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.