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Karate Club is an unsupervised machine learning extension library for NetworkX.

Karate Club consists of state-of-the-art methods to do unsupervised learning on graph structured data. To put it simply it is a Swiss Army knife for small-scale graph mining research. First, it provides network embedding techniques at the node and graph level. Second, it includes a variety of overlapping and non-overlapping commmunity detection methods. Implemented methods cover a wide range of network science (NetSci, Complenet), data mining (ICDM, CIKM, KDD), artificial intelligence (AAAI, IJCAI) and machine learning (NeurIPS, ICML, ICLR) conferences, workshops, and pieces from prominent journals.
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Benedek Rozemberczki 2020-01-25 15:51:44 +00:00 committed by GitHub
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@ -627,6 +627,7 @@ __Note:__ searching for ‘@’ will return all Twitter accounts listed on this
- [graph-tool](http://graph-tool.skewed.de/) - Python module for network manipulation and analysis, written mostly in C++ for speed.
- [graphviz](https://pypi.python.org/pypi/graphviz) - Python renderer for the DOT graph drawing language.
- [hiveplot](https://pypi.python.org/pypi/hiveplot) - Python utility for drawing networks as hive plots on matplotlib, a more comprehensive network visualization.
- [karateclub](https://github.com/benedekrozemberczki/karateclub) - Python package for unsupervised learning on graph structured data with a scikit-learn like API.
- [linkpred](https://github.com/rafguns/linkpred) - Assess the likelihood of potential links in a future snapshot of a network.
- [metaknowledge](http://networkslab.org/metaknowledge/) - Python package to turn bibliometrics data into authorship and citation networks.
- [networkx](http://networkx.github.io/) - Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.