发明名称 |
LARGE-SCALE ANOMALY DETECTION WITH RELATIVE DENSITY-RATIO ESTIMATION |
摘要 |
In one embodiment, a set of training data consisting of inliers may be obtained. A supervised classification model may be trained using the set of training data to identify outliers. The supervised classification model may be applied to generate an anomaly score for a data point. It may be determined whether the data point is an outlier based, at least in part, upon the anomaly score. |
申请公布号 |
US2016253598(A1) |
申请公布日期 |
2016.09.01 |
申请号 |
US201514634515 |
申请日期 |
2015.02.27 |
申请人 |
Yahoo! Inc. |
发明人 |
Yamada Makoto;Qin Chao;Ouyang Hua;Thomas Achint;Chang Yi |
分类号 |
G06N99/00 |
主分类号 |
G06N99/00 |
代理机构 |
|
代理人 |
|
主权项 |
1. A method, comprising:
obtaining a set of training data consisting of inliers; training a supervised classification model using the set of training data to identify outliers; applying the supervised classification model to generate an anomaly score for a data point; and determining whether the data point is an outlier based, at least in part, upon the anomaly score. |
地址 |
Sunnyvale CA US |