ScholarGate
Msaidizi
Machine learningMachine learning

Msitu wa Kutenga wa Mtandaoni

Msitu wa Kutenga wa Mtandaoni unapanua algorithm ya kugundua uhalifu ya Msitu wa Kutenga kwa data inayotiririka au inayowasili kila mara. Badala ya kujenga upya miti ya kutenga kutoka mwanzo wakati uchunguzi mpya unawasili, msitu unasasishwa hatua kwa hatua ili alama za uhalifu zibaki za sasa bila kusindika tena historia nzima. Hii huufanya kuwa wa vitendo kwa ufuatiliaji wa wakati halisi, ugunduzi wa ulaghai, na ufuatiliaji wa data ya sensor ambapo kiasi cha data huongezeka bila kikomo.

Fungua katika MethodMindHivi karibuniVideoHivi karibuniDownload slides

Soma mbinu kamili

Kwa wanachama pekee

Ingia kwa akaunti ya bure ili kusoma sehemu hii.

Ingia

Method map

The neighbourhood of related methods — select a node to explore.

Vyanzo

  1. Liu, F. T., Ting, K. M., & Zhou, Z.-H. (2008). Isolation Forest. In Proceedings of the 8th IEEE International Conference on Data Mining (ICDM), pp. 413–422. DOI: 10.1109/ICDM.2008.17
  2. Tan, S. C., Ting, K. M., & Liu, T. F. (2011). Fast Anomaly Detection for Streaming Data. In Proceedings of the 22nd International Joint Conference on Artificial Intelligence (IJCAI), pp. 1511–1516. link

Jinsi ya kunukuu ukurasa huu

ScholarGate. (2026, June 3). Online Isolation Forest (Streaming Anomaly Detection with Isolation Trees). ScholarGate. https://scholargate.app/sw/machine-learning/online-isolation-forest

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.

Compare side by side
ScholarGateOnline Isolation Forest (Online Isolation Forest (Streaming Anomaly Detection with Isolation Trees)). Imepatikana 2026-06-15 kutoka https://scholargate.app/sw/machine-learning/online-isolation-forest · Seti ya data: https://doi.org/10.5281/zenodo.20539026