les but this example.

loov = (KG^-1Y - diag(KG^-1)Y) / diag(I-KG^-1)

Let looe be the vector of prediction errors for each example
when the model was fitted with all examples but this example.

looe = y - loov = c / diag(G^-1)

The best score (negative mean squared error or user-provided scoring) is
stored in the `best_score_` attribute, and the selected hyperparameter in
`alpha_`.

References
----------
[1] http://cbcl.mit.edu/publications/ps/MIT-CSAIL-TR-2007-025.pdf
[2] https://www.mit.edu/~9.520/spring07/Classes/rlsslides.pdf
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