I am attempting to migrate some old python code using the scikit-Learn library.
When doing so I encountered the GaussianProcess class which is now fully reimplemented as GaussianProcessRegressor.
I was able to get a running script by replacing
self.f = GaussianProcess(corr='linear',theta0=1e-2,thetaL=1e-4,thetaU=1e-1)
with
self.f = GaussianProcessRegressor()
except now I have completely different results when calling predict()...
Any idea how to translate the autocorrelation method (corr) and different theta values with the new API?
I found this topic talking about pretty much the same problem, but aparently the author was fine about not having the old parameters taken into account, and this topic which states the problem precisely as well but does not provide a clear answer.