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...
| Published in: | Applied Soft Computing |
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| Main Author: | |
| Format: | Article |
| Language: | English |
| Published: |
Elsevier Ltd
2024
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| 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 |