Machine learning

Slaganje

Slaganje, ili složena generalizacija, je ansamblna metoda koju je uveo David Wolpert 1992. godine, a koja kombinira izlaze nekoliko različitih baznih modela (Razina-0) putem zasebnog meta-modela (Razina-1). Za razliku od bagginga i boostinga, ona namjerno koristi heterogene tipove modela i standardna je strategija završne faze u Kaggle natjecanjima.

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Method map

The neighbourhood of related methods — select a node to explore.

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Izvori

  1. Wolpert, D.H. (1992). Stacked Generalization. Neural Networks, 5(2), 241–259. DOI: 10.1016/S0893-6080(05)80023-1
  2. van der Laan, M.J., Polley, E.C. & Hubbard, A.E. (2007). Super Learner. Statistical Applications in Genetics and Molecular Biology, 6(1), Article 25. DOI: 10.2202/1544-6115.1309

Kako citirati ovu stranicu

ScholarGate. (2026, June 1). Stacked Generalization (Stacking Ensemble with a Meta-Learner). ScholarGate. https://scholargate.app/hr/machine-learning/stacking-ensemble

Which method?

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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Citirana u

ScholarGateStacking (Stacked Generalization (Stacking Ensemble with a Meta-Learner)). Preuzeto 2026-06-15 s https://scholargate.app/hr/machine-learning/stacking-ensemble · Skup podataka: https://doi.org/10.5281/zenodo.20539026