[scikit-learn] Markov Clustering?
t3kcit at gmail.com
Tue Dec 6 09:36:50 EST 2016
On 12/06/2016 08:05 AM, Allan Visochek wrote:
> At it's core, Markov clustering is a graph algorithm, it operates on a
> sparse similarity matrix (essentially, by simulating flow between the
> data points). This makes it useful for similarity graphs that don't
> originate from features (i.e. protien-protien interaction networks).
> Because the graph is based on similarity though, its definitely
> possible to use it as a data clustering algorithm that takes a
> similarity metric as an argument.
> I suppose it could be implemented so that the algorithm could take
> either a sparse similarity matrix or a set of features as its first
> argument. This would keep the same structure of the other clustering
> algorithms, but also allow use with pure similarity graphs. Does this
> make sense?
Yeah that's also how the other algorithms work.
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