Machine learningNetwork science

Bejzovski stohastički model blokova

Bejzovski stohastički model blokova (Bayesian SBM) je principijelan probabilistički metod za detekciju zajednica u mrežama. On tretira pripadnost grupi kao latentnu promenljivu i koristi Bejzovsko zaključivanje za istovremeno oporavljanje blok strukture i izbor broja zajednica, izbegavajući pristrasnost granične rezolucije koja pogađa pristupe zasnovane na modularnosti.

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Izvori

  1. Peixoto, T. P. (2014). Efficient Monte Carlo and greedy heuristic for the inference of stochastic block models. Physical Review E, 89(1), 012804. DOI: 10.1103/PhysRevE.89.012804
  2. Nowicki, K., & Snijders, T. A. B. (2001). Estimation and prediction for stochastic blockstructures. Journal of the American Statistical Association, 96(455), 1077–1087. DOI: 10.1198/016214501753208735

Kako citirati ovu stranicu

ScholarGate. (2026, June 3). Bayesian Stochastic Block Model (Bayesian SBM). ScholarGate. https://scholargate.app/sr/network-analysis/bayesian-stochastic-block-model

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ScholarGateBayesian Stochastic Block Model (Bayesian Stochastic Block Model (Bayesian SBM)). Preuzeto 2026-06-15 sa https://scholargate.app/sr/network-analysis/bayesian-stochastic-block-model · Skup podataka: https://doi.org/10.5281/zenodo.20539026