[scikit-learn] GPR intervals and MCMC
Quaglino Alessio
alessio.quaglino at usi.ch
Tue Nov 8 10:10:07 EST 2016
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
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.python.org/pipermail/scikit-learn/attachments/20161108/5b4090e0/attachment.html>
More information about the scikit-learn
mailing list