Machine learningNetwork science

Težinski stohastički blok model

Težinski stohastički blok model (W-SBM) proširuje klasični stohastički blok model na mreže čije su ivice numerički ponderisane. Pretpostavljajući da težine ivica između parova čvorova potiču iz distribucija koje zavise od pripadnosti tih čvorova blokovima, on istovremeno zaključuje particiju čvorova na zajednice i skup parametara težine od bloka do bloka — povraćajući strukturu nevidljivu metodama bez težine.

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Izvori

  1. Aicher, C., Jacobs, A. Z., & Clauset, A. (2014). Learning latent block structure in weighted networks. Journal of Complex Networks, 3(2), 221–248. DOI: 10.1093/comnet/cnu026
  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). Weighted Stochastic Block Model (W-SBM). ScholarGate. https://scholargate.app/sr/network-analysis/weighted-stochastic-block-model

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Citirana u

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