Invention Grant
- Patent Title: Holo-entropy adaptive boosting based anomaly detection
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Application No.: US16205138Application Date: 2018-11-29
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Publication No.: US11620180B2Publication Date: 2023-04-04
- Inventor: Zhen Mo , Bin Zan , Vijay Ganti , Vamsi Akkineni , HengJun Tian
- Applicant: VMware, Inc.
- Applicant Address: US CA Palo Alto
- Assignee: VMware, Inc.
- Current Assignee: VMware, Inc.
- Current Assignee Address: US CA Palo Alto
- Agency: Patterson + Sheridan, LLP
- Main IPC: G06F9/44
- IPC: G06F9/44 ; G06F11/07 ; G06F21/56 ; G06F11/34 ; G06N20/20 ; G06F9/455 ; H04L9/40

Abstract:
A computer-implemented method for determining whether data is anomalous includes generating a holo-entropy adaptive boosting model using, at least in part, a set of normal data. The holo-entropy adaptive boosting model includes a plurality of holo-entropy models and associated model weights for combining outputs of the plurality of holo-entropy models. The method further includes receiving additional data, and determining at least one of whether the additional data is normal or abnormal relative to the set of normal data or a score indicative of how abnormal the additional data is using, at least in part, the generated holo-entropy adaptive boosting model.
Public/Granted literature
- US20200174867A1 HOLO-ENTROPY ADAPTIVE BOOSTING BASED ANOMALY DETECTION Public/Granted day:2020-06-04
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