Your options are to either pick a clustering algorithm that supports a pre-computed distance matrix, or, find some kind of projection from C -> R, embed your data in R, then cluster your embedded data and transfer the labels back to C.
On Sat, Oct 19, 2019 at 11:44 AM ahmad qassemi <ahmadqass...@gmail.com> wrote: > Dear Mr/Mrs, > > I'm a PhD student in DS. I'm trying to use your provided code on *Spectral > CoClustering *and *Spectral Biclustering* to bi-cluster my data matrix ( > https://scikit-learn.org/stable/modules/biclustering.html). Since my data > has complex values, i.e., matrix elements are complex, your modules don't > work on my data. It seems that the reason is your K-means' code doesn't > work with complex numbers. I will really appreciate it if you take some > time and tell me how should I apply your codes on my complex data. Thanks a > lot in advance. > > Sincerely, > Ahmad Qassemi > _______________________________________________ > scikit-learn mailing list > scikit-learn@python.org > https://mail.python.org/mailman/listinfo/scikit-learn >
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