Since Gaussian Process returns a distribution and not a point estimate, why this example (and actually in every example with GP) talk about Confidence Intervals on the analogues for Bayesian statistics the Credible Intervals?
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I was wondering about that, too. My assumption is the following:
GaussianProcessRegressorfromsklearnimplements Algorithm 2.1 from Rasmussen & Williams (2006). Throughout this book, the ±2σ interval around µ is referred to as "95% confidence region". They simply do not make a distinction between "confidence" and "credible" region. I think the authors ofsklearnadopted that.C. E. Rasmussen & C. K. I. Williams, Gaussian Processes for Machine Learning, MIT Press, 2006