I have a discrete 3D density function, essentially a 3D histogram, and I'd
like to fit a GMM to it. From the documentation it appears that
sklearn.mixture.GMM wants raw data points - is it possible to give it the
histogram instead? Alternatively, it would work if I could use weighted
data points. Is this possible? Currently I'm able to sample points from the
histogram, but this is costly (and shouldn't be necessary).
Thanks,
Charles
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