Hi Quaglino,
You are right that at predict time both are not equivalent.
More specifically, in Eq 2.23 in http://www.gaussianprocess.
org/gpml/chapters/RW2.pdf
1. If you use a WhiteKernel, the first term becomes K^{hat}(X*, X) +
\sigma^2 where K^{hat} is the kernel that you are using apart from
Hello,
I am trying to understand if alpha is truly equivalent to WhiteKernel by
looking at gpr.py.
I can see that that the two are the same when fit() is called, i.e. self.L_ and
self.alpha_ are the same whether alpha or WhiteKernel is used.
In predict(), however, y_var = self.kernel_.diag(X)
