Training a supervised machine learning model for anomaly detection

US12388720B1 · kind B1 · utility

Assignee

• Elisa Oyj · FI

Inventors

• Adriana CHIS · Helsinki, FI
• Petteri Lunden · Espoo, FI

Key dates

• Filing date: Oct 4, 2023
• Grant date: Aug 12, 2025
• Expiry date: Oct 4, 2043

Classification

• Technology area (CPC H): Electricity
• CPC primary: H04L63/1425
• WIPO field: Digital communication
• WIPO sector: Electrical engineering

Abstract

Example embodiments may relate to training of a supervised machine learning model for anomaly detection in a communication network. A computer-implemented method may comprise: detecting, by an unsupervised machine learning model, a plurality of anomalies in performance indicator data of a communication network; receiving labels for a first subset of the plurality of anomalies and labelling the first subset of the plurality of anomalies with the labels; training, based on the labelled first subset of the plurality of anomalies, a semi-supervised machine learning model for labelling anomalies; labelling, by the semi-supervised machine learning model, a second subset of the plurality of anomalies; and training, based on the labelled first and second subsets of the plurality of anomalies, a supervised machine learning model for detecting and/or classifying anomalies in the performance indicator data.