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