One-Class SVM
One-class SVM ni algoriti ya ugunduzi wa anomali na ubunifu ambayo haijisimamiwi na hujifunza mpaka mkali unaozunguka data ya mafunzo ya kawaida katika nafasi ya vipengele iliyoanzishwa na kernel, ikionyesha uchunguzi mpya unaoanguka nje ya mpaka huo kama vipengee vya nje. Ilianzishwa na Scholkopf et al. mwaka 1999–2001, inapanua mfumo wa SVM kwa mazingira ya darasa moja ambapo hakuna anomali zilizowekwa lebo zinazopatikana.
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Vyanzo
- Scholkopf, B., Platt, J. C., Shawe-Taylor, J., Smola, A. J., & Williamson, R. C. (2001). Estimating the support of a high-dimensional distribution. Neural Computation, 13(7), 1443–1471. DOI: 10.1162/089976601750264965 ↗
- Tax, D. M. J., & Duin, R. P. W. (2004). Support vector data description. Machine Learning, 54(1), 45–66. DOI: 10.1023/B:MACH.0000008084.60811.49 ↗
Jinsi ya kunukuu ukurasa huu
ScholarGate. (2026, June 3). One-Class Support Vector Machine (Novelty and Anomaly Detection). ScholarGate. https://scholargate.app/sw/machine-learning/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.
- Uchambuzi wa kiotomatiki wa uhalifu (Autoencoder anomaly detection)Ujifunzaji wa Mashine↔ compare
- Isolation ForestUjifunzaji wa Mashine↔ compare
- Kielelezo cha Nje cha Mtaa (LOF)Ujifunzaji wa Mashine↔ compare
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