Interpretable supervised anomaly detection for determining reasons for unsupervised anomaly decision
US12333451B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 27, 2019 |
| Grant date | Jun 17, 2025 |
| Priority date | — |
| Expiry date | Dec 23, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N7/01
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Techniques are provided for determining reasons for unsupervised anomaly decisions. One method comprises obtaining values of predefined features associated with a remote user device; applying the predefined feature values to an unsupervised anomaly detection model that generates an unsupervised anomaly decision; applying the predefined feature values to a supervised anomaly detection model that generates a supervised anomaly decision; determining a third anomaly decision using the unsupervised anomaly decision; and determining reasons for the third anomaly decision by analyzing the supervised anomaly decision. The supervised anomaly detection model can be trained using the unsupervised anomaly decision and/or anomalous training data based on known anomalies. The third anomaly decision can be based on the supervised anomaly decision and the unsupervised anomaly decision using ensemble techniques.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.