The statistical machine learning framework.

The Data Generating Process (DGP) generates observable training data from the unobservable environmental probability distribution P(e). The learning machine observes the training data and uses its beliefs about the structure of the environmental probability distribution in order to construct a bestapproximating distribution P of the environmental distribution P(e). The resulting bestapproximating distribution of the environmental probability distribution supports decisions and behaviors by the learning machine for the purpose of improving its success when interacting with an environment characterized by uncertainty.