STAD-FEBTE, a shallow and supervised framework for time series anomaly detection by automatic feature engineering, balancing, and tree-based ensembles: An industrial case study
Author:
Affiliation:
1. Aalborg University,Robotics and Automation Group,Department of Materials and Production Eng.,Aalborg,Denmark
2. VELUX A/S,Global Production Technologies Group,Østbirk,Denmark
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10196083/10196094/10196288.pdf?arnumber=10196288
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5. XGBoost
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