# Seglearn: A Python Package for Learning Sequences and Time Series

## TL;DR

Seglearn is an open-source Python package that facilitates machine learning on sequences and time series data using sliding window segmentation, compatible with scikit-learn for classification, regression, and forecasting tasks.

## Contribution

It introduces a flexible pipeline for sequence learning that integrates with scikit-learn, simplifying the application of machine learning to time series data.

## Key findings

- Supports classification, regression, and forecasting
- Provides a flexible, scikit-learn compatible pipeline
- Includes comprehensive documentation and testing

## 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.