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[MRG+1] GaussianProcessRegressor: faster prediction of std #8591
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:
See this gist for benchmarking:
Even for medium size matrix, the new call is over 10x faster.