Hi Gael, Here are some suggestions regarding details of the page: - "Hierarchical clustering -> Few clusters": I thought it was not the best use case for these algorithms - "Hierarchical clustering -> even cluster size": this is not true if you consider single linkage, or even in general with Ward - You should at least refer to GMMs, as this is the most popular clustering framework that comes with a natural probabilistic setting - In the comparison table, you could also point that some methods require some -a priori random- initialization, while others do not. - "Geometry -> Distances between points": I'd rather call the column "Metric" and set it to "Euclidean" or "graph-based" - With mean shift, I would refer to 'modes' rather than 'blobs'.
See you, B On 03/25/2012 08:40 PM, Gael Varoquaux wrote: > Hi list, > > I am working on a summary table on clustering methods. It is not > finished, I need to do a bit more literature review, however, I'd love > some feedback on the current status: > https://github.com/GaelVaroquaux/scikit-learn/blob/master/doc/modules/clustering.rst > > Cheers, > > Gaël > > ------------------------------------------------------------------------------ > This SF email is sponsosred by: > Try Windows Azure free for 90 days Click Here > http://p.sf.net/sfu/sfd2d-msazure > _______________________________________________ > Scikit-learn-general mailing list > [email protected] > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general ------------------------------------------------------------------------------ This SF email is sponsosred by: Try Windows Azure free for 90 days Click Here http://p.sf.net/sfu/sfd2d-msazure _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
