AUC scores of anomaly detection algorithms.

<div><p>Anomaly detection plays a crucial role in fields such as information security and industrial production. It relies on the identification of rare instances that deviate significantly from expected patterns. Reliance on a single model can introduce uncertainty, as it may not adequa...

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Bibliographic Details
Main Author:	GaoXiang Zhao (21499525) (author)
Other Authors:	Lu Wang (45927) (author), Xiaoqiang Wang (194829) (author)
Published:	2025
Subjects:	Biotechnology Science Policy Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified random forest algorithm focal loss function empirical evaluations conducted conventional voting method mallows &# 8217 model averaging methods model averaging single model world datasets variability inherent results highlight rare instances paper proposes notable enhancement multiple models introduce uncertainty information security industrial production expected patterns effectively mitigate deviate significantly crucial role challenges posed base models anomaly detection adequately capture
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AUC scores of anomaly detection algorithms.

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