Online One-Class SVM
Online One-Class SVM je inkrementalno proširenje klasičnog One-Class Support Vector Machinea koje ažurira svoju granicu odlučivanja kako novi podaci pristižu uzorak po uzorak, čineći ga prikladnim za streaming okruženja i detekciju anomalija ili novosti u stvarnom vremenu bez ponovnog treniranja od nule.
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Method map
The neighbourhood of related methods — select a node to explore.
Izvori
- Laskov, P., Gehl, C., Krueger, S., & Muller, K.-R. (2006). Incremental support vector learning: Analysis, implementation and applications. Journal of Machine Learning Research, 7, 1909–1936. link ↗
- Scholkopf, B., Williamson, R., Smola, A., Shawe-Taylor, J., & Platt, J. (1999). Support vector method for novelty detection. Advances in Neural Information Processing Systems (NIPS), 12, 582–588. link ↗
Kako citirati ovu stranicu
ScholarGate. (2026, June 3). Online One-Class Support Vector Machine. ScholarGate. https://scholargate.app/hr/machine-learning/online-one-class-svm
Which method?
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.
- AutoenkoderDuboko učenje↔ compare
- Izolacijska šumaStrojno učenje↔ compare
- Lokalni faktor odstupanja (LOF)Strojno učenje↔ compare
- Jednoklasni SVMStrojno učenje↔ compare
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