Welcome to seglearn documentation!

This project is an sklearn extension for machine learning time series or sequences using a sliding window segmentation. It provides an integrated pipeline for segmentation, feature extraction, feature processing, and a final estimator compatible with sklearn model evaluation and parameter optimization tools.Seglearn provides a flexible approach to multivariate time series and contextual data for classification, regression, and forecasting problems.

See the source code repository on github: https://github.com/dmbee/seglearn

Getting started

Information to install, test, and contribute to the package.

User Guide

The main documentation. This contains an in-depth description of all algorithms and how to apply them.

API Documentation

The exact API of all functions and classes, as given in the docstring. The API documents expected types and allowed features for all functions, and all parameters available for the algorithms.

Examples

A set of examples illustrating the use of the different algorithms. It complements the User Guide.

About seglearn

Who we are, and how to cite us.

Indices and tables