Scikit-network: Graph analysis in python

被引：0

作者：

Bonald, Thomas ^{[1
]}

De Lara, Nathan ^{[1
]}

Lutz, Quentin ^{[1
]}

Charpentier, Bertrand ^{[2
]}

机构：

[1] Télécom Paris, Institut Polytechnique de Paris, Palaiseau,91120, France

[2] Technical University of Munich, Munich,D-80333, Germany

来源：

Journal of Machine Learning Research | 2020年 / 21卷

关键词：

Clustering algorithms - Graph theory - High level languages;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

Scikit-network is a Python package inspired by scikit-learn for the analysis of large graphs. Graphs are represented by their adjacency matrix in the sparse CSR format of SciPy. The package provides state-of-the-art algorithms for ranking, clustering, classifying, embedding and visualizing the nodes of a graph. High performance is achieved through a mix of fast matrix-vector products (using SciPy), compiled code (using Cython) and parallel processing. The package is distributed under the BSD license, with dependencies limited to NumPy and SciPy. It is compatible with Python 3.6 and newer. Source code, documentation and installation instructions are available online. ©2020 Thomas Bonald, Nathan de Lara, Quentin Lutz and Bertrand Charpentier.

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