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Makefile 0.34% Python 99.43% Batchfile 0.12% Shell 0.11%
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scikit-network's Introduction

logo sknetwork

Documentation Status

Python package for the analysis of large graphs:

  • Memory-efficient representation as sparse matrices in the CSR format of scipy
  • Fast algorithms
  • Simple API inspired by scikit-learn

Resources

Quick Start

Install scikit-network:

$ pip install scikit-network

Import scikit-network in a Python project:

import sknetwork as skn

See examples in the tutorials; the notebooks are available here.

Citing

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}
}

scikit-network's People

Contributors

alexisbarreaux avatar armand33 avatar fjsj avatar mlelarge avatar pi-r2 avatar pyup-bot avatar qlutz avatar r-jaylet avatar sharpenb avatar tbonald avatar tiphainev avatar victor-manach avatar

Watchers

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