Hello, I'd like to be able to cluster data using either k-means or mini-batch-kmeans for a toroidal geometry. I know that if I was using DBSCAN I could pass in a pre-computed distance matrix to do this; if I was using OPTICS I could pass in a 'metric' keyword for distance and specify a custom distance metric. Is this possible for K-means / minibatch-kmeans? I don't see distance metrics documented as possible keyword arguments... but perhaps they're allowed as **kwargs that pass to the underlying distance calculation call? Thanks, Shane
-- *PhD candidate & Research Assistant* *Cooperative Institute for Research in Environmental Sciences (CIRES)* *University of Colorado at Boulder* _______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
