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K-Nearest Neighbors Ensemble

K-Nearest Neighbors Ensemble (Ensemble KNN) menggabungkan beberapa model KNN — masing-masing dilatih dengan nilai k, metrik jarak, subset fitur, atau bootstrap data yang berbeda — dan mengagregasi prediksinya melalui pemungutan suara mayoritas (klasifikasi) atau perataan (regresi). Pendekatan ini mengurangi varians tinggi yang melekat pada model KNN tunggal mana pun dan menghasilkan prediksi yang lebih stabil dan akurat pada data tabular.

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Sumber

  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

Cara menyitasi halaman ini

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

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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 K-nearest neighbors (Ensemble K-Nearest Neighbors (Aggregated KNN)). Diakses 2026-06-15 dari https://scholargate.app/id/machine-learning/ensemble-k-nearest-neighbors · Set data: https://doi.org/10.5281/zenodo.20539026