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Objašnjivi K-najbližih susjeda

Objašnjivi K-najbližih susjeda (XKNN) nadograđuje klasični KNN klasifikator ili regresor strukturiranim post-hoc ili ugrađenim mehanizmima objašnjenja, otkrivajući koji su dohvaćeni susjedi, koje značajke i koji doprinosi udaljenosti pokreću svaku pojedinačnu predikciju — čineći obrazloženje modela transparentnim i revizibilnim za ljudske donositelje odluka.

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Izvori

  1. Cover, T. & Hart, P. (1967). Nearest neighbor pattern classification. IEEE Transactions on Information Theory, 13(1), 21–27. DOI: 10.1109/TIT.1967.1053964
  2. Papernot, N. & McDaniel, P. (2018). Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning. arXiv preprint arXiv:1803.04765. link

Kako citirati ovu stranicu

ScholarGate. (2026, June 3). Explainable K-Nearest Neighbors (XKNN). ScholarGate. https://scholargate.app/hr/machine-learning/explainable-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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Citirana u

ScholarGateExplainable K-Nearest Neighbors (Explainable K-Nearest Neighbors (XKNN)). Preuzeto 2026-06-15 s https://scholargate.app/hr/machine-learning/explainable-k-nearest-neighbors · Skup podataka: https://doi.org/10.5281/zenodo.20539026