[scikit-learn] Accessing Clustering Feature Tree in Birch

[Roman Yurchak]

 > 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-learn/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.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
>>
> _______________________________________________
> scikit-learn mailing list
> scikit-learn at python.org
> https://mail.python.org/mailman/listinfo/scikit-learn
>