| 发明名称 |
SEQUENTIAL ANOMALY DETECTION |
| 摘要 |
A dataset including at least one temporal event sequence is collected. A one-class sequence classifier f(x) that obtains a decision boundary is statistically learned. At least one new temporal event sequence is evaluated, wherein the at least one new temporal event sequence is outside of the dataset. It is determined whether the at least one new temporal event sequence is one of a normal sequence or an abnormal sequence based on the evaluation. Numerous additional aspects are disclosed. |
| 申请公布号 |
US2015052090(A1) |
申请公布日期 |
2015.02.19 |
| 申请号 |
US201313969151 |
申请日期 |
2013.08.16 |
| 申请人 |
International Business Machines Corporation |
发明人 |
Lin Ching-Yung;Song Yale;Wen Zhen |
| 分类号 |
G06N5/02;G06N99/00 |
主分类号 |
G06N5/02 |
| 代理机构 |
|
代理人 |
|
| 主权项 |
1. A method comprising:
collecting a dataset comprising at least one temporal event sequence; learning statistically a one-class sequence classifier f(x) that obtains a decision boundary; evaluating at least one new temporal event sequence, wherein the at least one new temporal event sequence is outside of the data set; and determining whether the at least one new temporal event sequence is one of a normal sequence or an abnormal sequence based on the evaluating step. |
| 地址 |
Armonk NY US |
