Adaptive threshold optimisation for online feature selection using dynamic particle swarm optimisation in determining feature relevancy and redundancy

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Adaptive threshold optimisation for online feature selection using dynamic particle swarm optimisation in determining feature relevancy and redundancy

In the era of data-driven decision-making, managing dynamic data streams characterised by evolving data distributions and high dimensionality presents a formidable challenge for online feature selection. This research addresses the challenge by developing innovative solutions in optimising Online Fe...

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Bibliographic Details
Published in:	Applied Soft Computing
Main Author:	Zaman E.A.K.; Ahmad A.; Mohamed A.
Format:	Article
Language:	English
Published:	Elsevier Ltd 2024
Online Access:	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85188509151&doi=10.1016%2fj.asoc.2024.111477&partnerID=40&md5=230522f6ff562abed0456ecd15c5c043

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