Typically when I think of limiting the number of points in a cluster I think of KD trees. I suppose that wouldn't work?
On Tue, Jul 11, 2017 at 11:22 AM, Ariani A <b.noush...@gmail.com> wrote: > ِDear Uri, > Thanks. I just have a pairwise distance matrix and I want to implement it > so that each cluster has at least 40 data points. (in Agglomerative). > Does it work? > Thanks, > -Ariani > > On Tue, Jul 11, 2017 at 1:54 PM, Uri Goren <u...@goren4u.com> wrote: > >> Take a look at scipy's fcluster function. >> If M is a matrix of all of your feature vectors, this code snippet should >> work. >> >> You need to figure out what metric and algorithm work for you >> >> from sklearn.metrics import pairwise_distance >> from scipy.cluster import hierarchy >> X = pairwise_distance(M, metric=metric) >> Z = hierarchy.linkage(X, algo, metric=metric) >> C = hierarchy.fcluster(Z,threshold, criterion="distance") >> >> Best, >> Uri Goren >> >> On Tue, Jul 11, 2017 at 7:42 PM, Ariani A <b.noush...@gmail.com> wrote: >> >>> Hi all, >>> I want to perform agglomerative clustering, but I have no idea of number >>> of clusters before hand. But I want that every cluster has at least 40 >>> data points in it. How can I apply this to sklearn.agglomerative >>> clustering? >>> Should I use dendrogram and cut it somehow? I have no idea how to relate >>> dendrogram to this and cutting it out. Any help will be appreciated! >>> I have to use agglomerative clustering! >>> Thanks, >>> -Ariani >>> >>> _______________________________________________ >>> scikit-learn mailing list >>> scikit-learn@python.org >>> https://mail.python.org/mailman/listinfo/scikit-learn >>> >>> >> >> >> -- >> >> >> *Uri Goren,Software innovator* >> >> *Phone: +972-507-649-650* >> >> *EMail: u...@goren4u.com <u...@goren4u.com>* >> *Linkedin: il.linkedin.com/in/ugoren/ <http://il.linkedin.com/in/ugoren/>* >> >> _______________________________________________ >> scikit-learn mailing list >> scikit-learn@python.org >> https://mail.python.org/mailman/listinfo/scikit-learn >> >> > > _______________________________________________ > scikit-learn mailing list > scikit-learn@python.org > https://mail.python.org/mailman/listinfo/scikit-learn > >
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