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Hi @nardi , unfortunately there is no faster way to do this at the moment. If you have an idea how to implement this efficiently, let me know! |
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I would like to perform a specific kind of sampling, and I'm not sure what is the best way to go about it. Say I have two variables (1d arrays)
X
andY
, and I have a GMM trained on the[X Y]
dataset. Now I'd like to generate values forY
based on an array of values ofX
, but instead of just getting the mean I'd like to obtain multiple (let's sayN
) values sampled according to the mixture distribution. One way to accomplish this is as follows:However, this requires a loop over all values of
X
(whichpredict
avoids). Is there a better/more performant way to get this same result?Beta Was this translation helpful? Give feedback.
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