Machine learningMachine learning

Bejzijano onlajn učenje

Bejzijano onlajn učenje primenjuje Bejzijanovu inferenciju sekvencijalno: svaki put kada stigne nova opservacija, trenutni aposteriorni raspored parametara modela postaje prior za sledeće ažuriranje. Rezultat je principijelan probabilistički okvir koji održava kalibrisane procene nesigurnosti tokom celog procesa, što ga čini pogodnim za postavke sa strimujućim i nestacionarnim podacima.

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Izvori

  1. Opper, M. (1998). A Bayesian approach to on-line learning. In D. Saad (Ed.), On-Line Learning in Neural Networks (pp. 363–378). Cambridge University Press. link
  2. Sato, M. (2001). Online model selection based on the variational Bayes. Neural Computation, 13(7), 1649–1681. DOI: 10.1162/089976601750265045

Kako citirati ovu stranicu

ScholarGate. (2026, June 3). Bayesian Online Learning (Sequential Posterior Update). ScholarGate. https://scholargate.app/sr/machine-learning/bayesian-online-learning

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Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.

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ScholarGateBayesian Online Learning (Bayesian Online Learning (Sequential Posterior Update)). Preuzeto 2026-06-15 sa https://scholargate.app/sr/machine-learning/bayesian-online-learning · Skup podataka: https://doi.org/10.5281/zenodo.20539026