Machine learningMachine learning

Ensemble K-Nearest Neighbors (Ensemble KNN)

Ensemble K-Nearest Neighbors kombinuje više KNN modela — svaki obučen sa različitom vrednošću k, metrikom rastojanja, podskupom atributa iliждый bootstrap uzorkom podataka — i agregira njihove predikcije glasanjem većine (klasifikacija) ili prosekovanjem (regresija). Ovaj pristup smanjuje visoku varijansu inherentnu za svaki pojedinačni KNN model i daje stabilnije, preciznije predikcije na tabelarnim podacima.

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Izvori

  1. Domeniconi, C., & Yan, B. (2004). Nearest neighbor ensemble. In Proceedings of the 17th International Conference on Pattern Recognition (ICPR), Vol. 1, pp. 228–231. IEEE. DOI: 10.1109/ICPR.2004.1334065
  2. Zhou, Z.-H. (2012). Ensemble Methods: Foundations and Algorithms. Chapman and Hall/CRC. ISBN: 978-1-4398-3003-1

Kako citirati ovu stranicu

ScholarGate. (2026, June 3). Ensemble K-Nearest Neighbors (Aggregated KNN). ScholarGate. https://scholargate.app/sr/machine-learning/ensemble-k-nearest-neighbors

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ScholarGateEnsemble K-nearest neighbors (Ensemble K-Nearest Neighbors (Aggregated KNN)). Preuzeto 2026-06-15 sa https://scholargate.app/sr/machine-learning/ensemble-k-nearest-neighbors · Skup podataka: https://doi.org/10.5281/zenodo.20539026