+1
What about adding an option like "compress_children" or similar to ward_tree()
that results in the normal output for children_ if True, e.g. for 3 data
instances it outputs
[[0,1], # 0 and 1 are merged in node 3
[2, 3]] # 2 is merged with node 3
For False, it would expand the output for children_ into
[[0,1], 2]
wr
2013/1/27 Satrajit Ghosh <[email protected]>
> hi all,
>
> i think it would be good to describe how to use the output from ward_tree,
> especially for hierarchical clustering (currently it appears non-obvious).
> for example, how do i get the tree height?
> i saw there was an open pr on refactoring that enterprise, but it appears
> to be abandoned.
>
> for example, having a utility function that returned the cluster labels at
> a given tree height would be useful. i'm now checking the scipy hierachical
> stuff to see if it makes sense for that package to simply use what's
> already in scipy. would it make sense to simply wrap the scipy routines
> within the context of the sklearn api?
>
> cheers,
>
> satra
>
>
>
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