[scikit-learn] GPR intervals and MCMC

[Quaglino Alessio]

Hello,

I am using scikit-learn 0.18 for doing GP regressions. I really like it and all works great, but I am having doubts concerning the confidence intervals computed by predict(X,return_std=True):

- Are they true confidence intervals (i.e. of the mean / latent function) or they are in fact prediction intervals? I tried computing the prediction intervals using sample_y(X) and I get the same answer as that returned by predict(X,return_std=True).

- My understanding is therefore that scikit-learn is not fully Bayesian, i.e. it does not compute probability distributions for the parameters, but rather the values that maximize the likelihood?

- If I want the confidence interval, is my best option to use an external MCMC optimizer such as PyMC?

Thank you in advance!

Regards,
-------------------------------------------------
Dr. Alessio Quaglino
Postdoctoral Researcher
Institute of Computational Science
Università della Svizzera Italiana






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