Free software library in Python for machine learning on graphs:
- Memory-efficient representation of graphs as sparse matrices in scipy format
- Fast algorithms
- Simple API inspired by scikit-learn
- Free software: BSD license
- GitHub: https://github.com/sknetwork-team/scikit-network
- Documentation: https://scikit-network.readthedocs.io
Install scikit-network:
$ pip install scikit-network
Import scikit-network:
import sknetwork
An overview of the package is presented in this notebook.
The documentation is structured as follows:
- Getting started: First steps to install, import and use scikit-network.
- User manual: Description of each function and object of scikit-network.
- Tutorials: Application of the main tools to toy examples.
- Examples: Examples combining several tools on specific use cases.
- About: Authors, history of the library, how to contribute, index of functions and objects.
If you want to cite scikit-network, please refer to the publication in the Journal of Machine Learning Research:
@article{JMLR:v21:20-412,
author = {Thomas Bonald and Nathan de Lara and Quentin Lutz and Bertrand Charpentier},
title = {Scikit-network: Graph Analysis in Python},
journal = {Journal of Machine Learning Research},
year = {2020},
volume = {21},
number = {185},
pages = {1-6},
url = {http://jmlr.org/papers/v21/20-412.html}
}