One-Class Conditional Random Fields for Sequential Anomaly Detection
Sequential anomaly detection is a challenging problem due to the one-class nature of the data (i.e., data is collected from only one class) and the temporal dependence in sequential data. We present One-Class Conditional Random Fields (OCCRF) for sequential anomaly detection that learn from a one-cl...
| Main Authors: | , , , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Association for Computing Machinery (ACM)
2014
|
| Online Access: | http://hdl.handle.net/1721.1/86065 https://orcid.org/0000-0001-5232-7281 |