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\u2019 rule.<\/p>\n
See Bayes rule, Learning<\/a>, Posterior distribution<\/a>, Prior distribution<\/a>, Statistical learning<\/a><\/p>\n <\/body><\/html><\/p>\n","protected":false},"excerpt":{"rendered":" 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\u2019 … <\/p>\n