[scikit-learn] Clustering 4 dimensional data

Dmitry Ignatov dmitrii.ignatov at gmail.com
Mon Feb 27 23:35:01 EST 2017


Sometimes, when you need to find homogeneous subtensors, you can refer to
it as multimodal clustering, an extension of biclustering. I cannot see
clearly whether this is the case here.

28 февр. 2017 г. 6:54 пользователь "Joel Nothman" <joel.nothman at gmail.com>
написал:

What do your four dimensions mean? Can you reshape your data such that it
can be seen as a collection of 1d vectors drawn independently from some
distribution?

On 28 February 2017 at 14:43, Rohan Koodli <rovik05 at gmail.com> wrote:

> I'm having trouble understanding how to cluster multidimensional data.
> Specifically, a 4 dimensional array.
>
>
> test = [[[[3,10],[1,5],[3,18]],[[3,1],[0,0],[0,0]],[[3,3],[1,5],[0,0]]],[[[1,5],[2,7],[0,0]],[[1,7],[0,0],[0,0]],[[0,0],[0,0],[0,0]]]]
>
> from sklearn import mixture
> gmm = mixture.GMM()
> gmm.fit(test)
>
> The code returns the following error:
>
> "Found array with dim 4. GMM expected <= 2."
>
> Do I need to change the way my data is formatted? Is there a way of doing
> clustering on 4 dimensional data?
>
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