The key idea behind the probabilistic framework to machine learning is that learning can be thought of as inferring plausible models to explain observed data. A machine can use such models to make ...

This is a preview. Log in through your library . Abstract Objectives-To take the common "Bayesian" interpretation of conventional confidence intervals to its logical conclusion, and hence to derive a ...