[scikit-learn] Accessing Clustering Feature Tree in Birch

[Suzen, Mehmet]

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.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.
>
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