Hi,
I wanted to learn Gaussian Mixture with "weighted samples" as I am trying
to run the algorithm in the paper of learning mixture models with Coreset:
http://papers.nips.cc/paper/4363-scalable-training-of-mixture-models-via-coresets
(this paper has some typos in the algorithm sections).
If I'm not missing, I've found that the current GMM implementation does not
support learning from weighted samples. I'm not sure whether how many
people want this feature implemented, but I hope I can contribute to scikit
by implementing it and use it for myself at least.
Before starting the implementation, I want to hear opinions of developers
of scikit about implementing this, as guided in the developers contribution
page.
Best regards,
Ji Oh
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