Microsoft Corporation
DATA ANOMALY DETECTION
Last updated:
Abstract:
Systems and methods for data anomaly detection include recommending one or more algorithms from a set of algorithms to process received time series data, wherein the one or more algorithms are recommended based at least in part on a type of workload for processing the received time series data. Assisted parameter tuning is provided for a detected anomaly alert and calibration, and the received time series data is processed based on a user selected algorithm that is parameter tuned, thereby resulting in more efficient and reliable anomaly detection.
Status:
Application
Type:
Utility
Filling date:
13 May 2022
Issue date:
25 Aug 2022