Machine learningMachine learning

Ensemble Online Learning

Ensemble Online Learning kombinira više baznih modela koji se inkrementalno treniraju na toku podataka, ažurirajući svaki model po jednu opservaciju. Agregiranjem predikcija raznolikih online modela, ansambl postiže točnost i robusnost koji nadmašuju bilo koji pojedinačni inkrementalni model, istovremeno se kontinuirano prilagođavajući promjenjivim distribucijama podataka.

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Izvori

  1. Oza, N. C., & Russell, S. (2001). Online bagging and boosting. In Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics (AISTATS 2001), pp. 229–236. link
  2. Online machine learning. Wikipedia. link

Kako citirati ovu stranicu

ScholarGate. (2026, June 3). Ensemble Online Learning (Online Ensemble Methods). ScholarGate. https://scholargate.app/hr/machine-learning/ensemble-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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ScholarGateEnsemble Online Learning (Ensemble Online Learning (Online Ensemble Methods)). Preuzeto 2026-06-15 s https://scholargate.app/hr/machine-learning/ensemble-online-learning · Skup podataka: https://doi.org/10.5281/zenodo.20539026