Online Anomaly Detection Based on Support Vector Clustering
A two-phase online anomaly detection method based on support vector clustering (SVC) in the presence of non-stationary data is developed in this paper which permits arbitrary-shaped data clusters to be precisely treated. In the first step, offline learning is performed to achieve an appropriate dete...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Atlantis Press
2015-08-01
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| Series: | International Journal of Computational Intelligence Systems |
| Subjects: | |
| Online Access: | https://www.atlantis-press.com/article/25868625.pdf |