Per the example here: http://scikit-learn.org/stable/auto_examples/text/document_clustering.html
if your inputs are normalized, sklearn's kmeans behaves like sperical kmeans (unless I'm misunderstanding something, which is certainly possible, caveat lector, &c )... On Jun 27, 2016 12:13 PM, "Michael Eickenberg" <[email protected]> wrote: > hmm, not an answer, and off the top of my head: > if you normalize your data points to l2 norm equal 1, and then use > standard kmeans with euclidean distance (which then amounts to 2 - 2 > cos(angle between points)) would this be enough for your purposes? (with a > bit of luck there may even be some sort of correspondence) > > Michael > > On Monday, June 27, 2016, JAGANADH G <[email protected]> wrote: > >> Hi , >> is there any Python package available for experiment with Sperical Kmeans >> ? >> >> >> -- >> ********************************** >> JAGANADH G >> http://jaganadhg.in >> *ILUGCBE* >> http://ilugcbe.org.in >> > > _______________________________________________ > scikit-learn mailing list > [email protected] > https://mail.python.org/mailman/listinfo/scikit-learn > >
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