Process of learning by means ofprobabilistic Bayesian inferences. In Bayesian learning, current knowledge isrepresented as a set of hypotheses with a probability distribution (priorprobabilities, or shortly priors). Learning consists in observing evidence andre-estimating probability distribution of the hypotheses given the observedevidence (thus creating posterior probabilities). The inference that generatesposterior probability of each hypothesis follows Bayes’ rule.
See Bayes rule, Learning, Posterior distribution, Prior distribution, Statistical learning