Hi, I'd like to propose a couple of features that, as a user, I believe may be useful for Gaussian mixture modeling with GaussianMixture. I don't see how to currently do them, and I think they should be quite easy to implement, but I may be wrong.
1. The weights of the components may be known. In that case, we would like to provide them through weights_init, but then they should be frozen and not optimized by the EM steps. So perhaps a frozen_weights boolean parameter, relevant only when weights_init is not None? 2. In covariance_type, there are the full/diag/spherical options, but I think that logically "tied" is independent - currently it's "tied full", but there could just as well be "tied diag" and even "tied spherical" with only a single parameter for the variances. So I propose having two input parameters allowing for 3*2 = 6 structures instead of the current 4. Thanks for all your great work for the community, Ehud Schreiber.
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