Multi-type concept drift detection under a dual-layer variable sliding window in frequent pattern mining with cloud computing

Multi-type concept drift detection under a dual-layer variable sliding window in frequent pattern mining with cloud computing

Abstract The detection of different types of concept drift has wide applications in the fields of cloud computing and security information detection. Concept drift detection can indeed assist in promptly identifying instances where model performance deteriorates or when there are changes in data dis...

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Bibliographic Details
Main Authors: Jing Chen, Shengyi Yang, Ting Gao, Yue Ying, Tian Li, Peng Li
Format: Article
Language:English
Published: SpringerOpen 2024-02-01
Series:Journal of Cloud Computing: Advances, Systems and Applications
Subjects:
Data Stream
Frequent Pattern Mining (FPM)
Dual-layer Variable Sliding Window
Concept Drift Detection (CDD)
Cloud Computing
Online Access:https://doi.org/10.1186/s13677-023-00566-9

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