Anomaly Detection Using Ensemble Classification and Evidence Theory

Anomaly Detection Using Ensemble Classification and Evidence Theory

Multi-class ensemble classification remains a popular focus of investigation within the research community. The popularization of cloud services has sped up their adoption due to the ease of deploying large-scale machine-learning models. It has also drawn the attention of the industrial sector becau...

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Bibliographic Details
Main Authors: Fernando Aravalo, M. Tahasanul Ibrahim, M. P. Christian Alison, Andreas Schwung
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Multi-class classification
ensemble classifier
evidence theory
pool selection
uncertainty quantification
anomaly detection
Online Access:https://ieeexplore.ieee.org/document/10135082/

Internet

https://ieeexplore.ieee.org/document/10135082/

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