Automatic Data Selection for Machine Learning based Anomaly Detection
Description
We develop and test a novel method for a fully unsupervised selection of appropriate training data for anomaly detection using machine learning methods.
Key Data
Projectlead
Project team
Jannik Zgraggen
Project status
completed, 09/2021 - 08/2022
Funding partner
Internal
Technikumstrasse 81
8400 Winterthur