Two Outlier-Sensitive Measures for Semi-supervised Dynamic Ensemble Anomaly Detection Models-Reference-Cited by-同舟云学术

Two Outlier-Sensitive Measures for Semi-supervised Dynamic Ensemble Anomaly Detection Models

Published:2022-09-01 Issue: Volume: Page:
ISSN:1370-4621
Container-title:Neural Processing Letters
language:en
Short-container-title:Neural Process Lett

Author:

Fu Shiyuan,Gao Xin^ORCID,Li Baofeng,Xue Bing,Jia Xin,Huang Zijian,Zhang Guangyao,Huang Xu

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Networks and Communications,General Neuroscience,Software

Link

https://link.springer.com/content/pdf/10.1007/s11063-022-11017-y.pdf

Reference34 articles.

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3. Antosik B, Kurzynski M (2011) New measures of classifier competence-heuristics and application to the design of multiple classifier systems. In: Computer recognition systems 4. Springer, Berlin, pp 197–206. https://doi.org/10.1007/978-3-642-20320-6_21

4. Chandola V, Banerjee A, Kumar V (2009) Anomaly detection: a survey. ACM Comput Surv 41(3):1–58. https://doi.org/10.1145/1541880.1541882

5. Chen Y, Zhou XS, Huang TS (2001) One-class SVM for learning in image retrieval. In: Proceedings 2001 international conference on image processing, IEEE, pp 34–37. https://doi.org/10.1109/ICIP.2001.958946

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