# [scikit-learn] What is the FeatureAgglomeration algorithm?

Raphael C drraph at gmail.com
Thu Jul 26 01:25:44 EDT 2018

```Is it expected that all three linkages options should give the same result
in my toy example?

Raphael

On Thu, 26 Jul 2018 at 06:20 Gael Varoquaux <gael.varoquaux at normalesup.org>
wrote:

> algorithms, depending on the choice of "linkage". These are well
> documented in the literature, or on wikipedia.
>
> Gaël
>
> On Thu, Jul 26, 2018 at 06:05:21AM +0100, Raphael C wrote:
> > Hi,
>
> > I am trying to work out what, in precise mathematical terms,
> > [FeatureAgglomeration][1] does and would love some help. Here is some
> example
> > code:
>
>
> >     import numpy as np
> >     from sklearn.cluster import FeatureAgglomeration
> >     for S in ['ward', 'average', 'complete']:
> >         print(FA.fit_transform(np.array([[-50,6,6,7,], [0,1,2,3]])))
>
> > This outputs:
>
> >
>
> >     [[  6.33333333 -50.        ]
> >      [  2.           0.        ]]
> >     [[  6.33333333 -50.        ]
> >      [  2.           0.        ]]
> >     [[  6.33333333 -50.        ]
> >      [  2.           0.        ]]
>
> > Is it possible to say mathematically how these values have been computed?
>
> > Also, what exactly does linkage do and why doesn't it seem to make any
> > difference which option you choose?
>
> > Raphael
>
>
> >   [1]: http://scikit-learn.org/stable/modules/generated/
> > sklearn.cluster.FeatureAgglomeration.html
>
> > PS I also asked at
> > https://stackoverflow.com/questions/51526616/
> >
>
>
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>
>
> --
>     Gael Varoquaux
>     Senior Researcher, INRIA Parietal
>     NeuroSpin/CEA Saclay , Bat 145, 91191 Gif-sur-Yvette France
>     Phone:  ++ 33-1-69-08-79-68