Hey,
I wanted to see that for a long time, too. :) If you'd plan on
implementing this, I could contribute.
However, I am not too familiar with variational inference for the GPs
which is what you would need I guess.
Or do you think it is feasible to compute the full kernel for the GP?
Cheers,
S
Am 01.02.18 um 20:01 schrieb Valeriy Avanesov:
Hi all,
it came to my surprise that there is no implementation of Gaussian
Process in Spark MLlib. The approach is widely known, employed and
scalable (its sparse versions). Is there a good reason for that? Has
it been discussed before?
If there is a need in this approach being a part of MLlib I am eager
to contribute.
Best,
Valeriy.
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