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" <[email protected]> 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 <[email protected]> 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? > > _______________________________________________ > scikit-learn mailing list > [email protected] > https://mail.python.org/mailman/listinfo/scikit-learn > > _______________________________________________ scikit-learn mailing list [email protected] https://mail.python.org/mailman/listinfo/scikit-learn
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