[MRG+1] GaussianProcessRegressor: faster prediction of std #8591
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LGTM |
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LGTM, can you add an entry in doc/whats_new.rst? |
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Done :-) |
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Merging, thanks a lot! |
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Reference Issue
None
What does this implement/fix? Explain your changes.
Predicting the std in GaussianProcessRegressor is very slow because of a particular np.einsum call. Simplifying the call gives the same result much faster.
Any other comments?
See this SO thread for a very similar situation solved the same way:
http://stackoverflow.com/questions/14758283/is-there-a-numpy-scipy-dot-product-calculating-only-the-diagonal-entries-of-the
See this gist for benchmarking:
https://gist.github.com/hbertrand/191f94fc2a7b2c14a6a6739e9a5afe45
Even for medium size matrix, the new call is over 10x faster.