Machine learningMachine learning

Online model Gaussovih smjesa

Online model Gaussovih smjesa prilagođava klasični GMM podatkovnim nizovima ili velikim skupovima podataka zamjenom EM algoritma punog paketa inkrementalnim ažuriranjima — obradom jedne opservacije ili mini-paketa odjednom i kontinuiranim usavršavanjem srednjih vrijednosti, kovarijanci i težina komponenti bez ponovnog prolaska kroz cijeli skup podataka.

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Izvori

  1. Cappé, O. & Moulines, E. (2009). On-line expectation-maximization algorithm for latent data models. Journal of the Royal Statistical Society: Series B, 71(3), 593–613. DOI: 10.1111/j.1467-9868.2009.00698.x
  2. Sato, M. & Ishii, S. (2000). On-line EM algorithm for the normalized Gaussian network. Neural Computation, 12(2), 407–432. DOI: 10.1162/089976600300015853

Kako citirati ovu stranicu

ScholarGate. (2026, June 3). Online Gaussian Mixture Model (Incremental / Streaming GMM). ScholarGate. https://scholargate.app/hr/machine-learning/online-gaussian-mixture-model

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ScholarGateOnline Gaussian Mixture Model (Online Gaussian Mixture Model (Incremental / Streaming GMM)). Preuzeto 2026-06-15 s https://scholargate.app/hr/machine-learning/online-gaussian-mixture-model · Skup podataka: https://doi.org/10.5281/zenodo.20539026