A survey on machine learning for recurring concept drifting data streams

作者：

Highlights：

• A comprehensive survey of techniques to deal with recurring changes in data streams.

• Review of recent approaches for model reuse and meta learning on data streams.

• Analysis of open challenges and future research trends.

摘要

•A comprehensive survey of techniques to deal with recurring changes in data streams.•Review of recent approaches for model reuse and meta learning on data streams.•Analysis of open challenges and future research trends.

论文关键词：Regime change,Online machine learning,Data streams,Concept drift,Meta learning

论文评审过程：Received 21 May 2022, Revised 19 September 2022, Accepted 27 September 2022, Available online 3 October 2022, Version of Record 11 October 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.118934