Machine learning-based selection of metrics for anomaly detection
US12073182B2 · kind B2 · utility
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20Claims
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Key dates
| Filing date | Jul 17, 2023 |
| Grant date | Aug 27, 2024 |
| Priority date | — |
| Expiry date | Jul 17, 2043 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L43/024
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
A plurality of metrics records, including some records indicating metrics for which anomaly analysis has been performed, is obtained. Using a training data set which includes the metrics records, a machine learning model is trained to predict an anomaly analysis relevance score for an input record which indicates a metric name. Collection of a particular metric of an application is initiated based at least in part on an anomaly analysis relevance score obtained for the particular metric using a trained version of the model.
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