Hi Roman,
Thank you for the detailed and informative answer.
On Mon, Oct 2, 2017 at 12:14 PM, Roman Yurchak
wrote:
> Hello,
>
> sklearn.cluster.Birch follows the original BIRCH paper, that appears to be
> mostly focused on efficiently building the hierarchical clustering
Hello,
sklearn.cluster.Birch follows the original BIRCH paper, that appears to
be mostly focused on efficiently building the hierarchical clustering
tree (and not so much on making the later analysis user friendly). The
attributes exposed by Birch are those that could be reasonably exposed
I need this information to use it in a scientific study and
I think that a function interface would make this easier.
Thank you for your answer.
On Sat, Sep 16, 2017 at 1:53 PM, Joel Nothman
wrote:
> There is no such thing as "the data samples in this cluster". The
There is no such thing as "the data samples in this cluster". The point of
Birch being online is that it loses any reference to the individual samples
that contributed to each node, but stores some statistics on their basis.
Roman Yurchak has, however, offered a PR where, for the non-online case,
I'd be interested in hearing the answer to this as well, specifically if
there's a standardized way in the API for dealing with nested
hierarchical clusters (i.e., when 'b' and 'c' are child clusters totally
contained within parent cluster 'a').
Perhaps there's a way to identify multiple
Dear scikit-learn members,
I have written about this subject before but I have not completely solved
my question.
- 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
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
wrote:
> > what are the
> 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
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?