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As this tutorial introduces the spectral clustering method that uses a similarity matrix between objects, I believe graph clustering methods are also worth ment
by scoresmoke 5y ago
As this tutorial introduces the spectral clustering method that uses a similarity matrix between objects, I believe graph clustering methods are also worth mentioning. When I was investigating this topic, I released an implementation of a very efficient randomized clustering algorithm for graphs called Chinese Whispers: https://github.com/nlpub/chinese-whispers-python https://github.com/nlpub/chinese-whispers-python. Since it does not use matrices internally, it allows handling very large NetworkX graphs.
- zwaps 5y agoHere is another Python graph clustering library, also based on networkX. This one works well for similarity style graphs - dense, weighted and directed graphs, such as what you would get from deriving distances for instances of other data: https://github.com/IngoMarquart/python-threshold-clustering https://github.com/IngoMarquart/python-threshold-clustering