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.

Status:
Grant
Type:

Utility

Filling date:

14 Jan 2019

Issue date:

24 May 2022