Machine learningMachine learning

Polu-nadgledani K-sredina

Polu-nadgledani K-sredina proširuje standardno K-sredina grupiranje uključivanjem djelomičnog nadzora — bilo malog skupa označenih sjemenih točaka ili parnih ograničenja mora-povezati i ne-može-povezati — za vođenje formiranja klastera. Prelazi s nenadgledanog grupiranja na potpuno nadgledanu klasifikaciju, omogućujući smislenije klastere kada su oznake oskudne, ali skupe za potpuno dobivanje.

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Izvori

  1. Wagstaff, K., Cardie, C., Rogers, S., & Schroedl, S. (2001). Constrained K-means Clustering with Background Knowledge. In Proceedings of the 18th International Conference on Machine Learning (ICML 2001), pp. 577–584. link
  2. Basu, S., Banerjee, A., & Mooney, R. J. (2002). Semi-supervised Clustering by Seeding. In Proceedings of the 19th International Conference on Machine Learning (ICML 2002), pp. 27–34. link

Kako citirati ovu stranicu

ScholarGate. (2026, June 3). Semi-supervised K-means Clustering. ScholarGate. https://scholargate.app/hr/machine-learning/semi-supervised-k-means

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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

ScholarGateSemi-supervised K-means (Semi-supervised K-means Clustering). Preuzeto 2026-06-15 s https://scholargate.app/hr/machine-learning/semi-supervised-k-means · Skup podataka: https://doi.org/10.5281/zenodo.20539026