Invention Grant
- Patent Title: Large-scale anomaly detection with relative density-ratio estimation
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Application No.: US14634515Application Date: 2015-02-27
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Publication No.: US10909468B2Publication Date: 2021-02-02
- Inventor: Makoto Yamada , Chao Qin , Hua Ouyang , Achint Thomas , Yi Chang
- Applicant: Oath Inc.
- Applicant Address: US NY New York
- Assignee: Oath Inc.
- Current Assignee: Oath Inc.
- Current Assignee Address: US NY New York
- Agency: Cooper Legal Group, LLC
- Main IPC: G06F21/55
- IPC: G06F21/55 ; G06N20/00

Abstract:
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.
Public/Granted literature
- US20160253598A1 LARGE-SCALE ANOMALY DETECTION WITH RELATIVE DENSITY-RATIO ESTIMATION Public/Granted day:2016-09-01
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