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Online K-means

Online K-means er en strømmende variant av den klassiske K-means-algoritmen som oppdaterer klyngesentroidene én observasjon om gangen – eller i små mini-batcher – uten å lagre hele datasettet i minnet. Den er spesielt egnet for store, sanntids- eller kontinuerlig ankommende data der batch-rekalkulering ville være for langsom eller upraktisk.

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Kilder

  1. MacQueen, J. (1967). Some methods for classification and analysis of multivariate observations. In Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, Vol. 1, pp. 281–297. University of California Press. link
  2. Sculley, D. (2010). Web-scale k-means clustering. In Proceedings of the 19th International Conference on World Wide Web (WWW 2010), pp. 1177–1178. ACM. DOI: 10.1145/1772690.1772862

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ScholarGate. (2026, June 3). Online K-means Clustering (Sequential / Streaming K-means). ScholarGate. https://scholargate.app/no/machine-learning/online-k-means

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Referert av

ScholarGateOnline K-means (Online K-means Clustering (Sequential / Streaming K-means)). Hentet 2026-06-15 fra https://scholargate.app/no/machine-learning/online-k-means · Datasett: https://doi.org/10.5281/zenodo.20539026