Dear Roman, I tried to search through on the web but i didn't get any information or example.
Could you give me an example of using _CFNode.centroids_? I would appreciate it if you would help me. On Wed, Aug 23, 2017 at 2:28 PM, Roman Yurchak <rth.yurc...@gmail.com> wrote: > > what are the data samples in this cluster > > Mehmet's response below works for exploring the hierarchical tree. > However, Birch currently doesn't store the data samples that belong to a > given subcluster. If you need that, as far as I know, a reasonable > approximation can be obtained by computing the data samples that are > closest to the centroid of the considered subcluster (accessible via > _CFNode.centroids_) as compared to all other subcluster centroids at this > hierarchical tree depth. > > Alternatively, the modifications in PR https://github.com/scikit-lear > n/scikit-learn/pull/8808 aimed to make this process easier.. > -- > Roman > > > On 23/08/17 13:44, Suzen, Mehmet wrote: > >> Hi Sema, >> >> You can access CFNode from the fit output, assign fit output, so you >> can have the object. >> >> brc_fit = brc.fit(X) >> brc_fit_cfnode = brc_fit.root_ >> <sklearn.cluster.birch._CFNode object at 0x7ff31acbf668> >> >> Then you can access CFNode, see here >> https://kite.com/docs/python/sklearn.cluster.birch._CFNode >> >> Also, this example comparing mini batch kmeans. >> http://scikit-learn.org/stable/auto_examples/cluster/plot_ >> birch_vs_minibatchkmeans.html >> >> Hope this was what you are after. >> >> Best, >> Mehmet >> >> On 23 August 2017 at 10:55, Sema Atasever <s.atase...@gmail.com> wrote: >> >>> Dear scikit-learn members, >>> >>> Considering the "CF-tree" data structure : >>> >>> - How can i access Clustering Feature Tree in Birch? >>> >>> - For example, how many clusters are there in the hierarchy under the >>> root >>> node and what are the data samples in this cluster? >>> >>> - Can I get them separately for 3 trees? >>> >>> Best. >>> >>> _______________________________________________ >>> 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 >> >> > _______________________________________________ > scikit-learn mailing list > scikit-learn@python.org > https://mail.python.org/mailman/listinfo/scikit-learn >
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