[scikit-learn] Accessing Clustering Feature Tree in Birch

Suzen, Mehmet msuzen at gmail.com
Wed Aug 23 06:44:58 EDT 2017

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

Also, this example comparing mini batch kmeans.

Hope this was what you are after.


On 23 August 2017 at 10:55, Sema Atasever <s.atasever at 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 at python.org
> https://mail.python.org/mailman/listinfo/scikit-learn

More information about the scikit-learn mailing list