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...
| Published in: | APPLIED SOFT COMPUTING |
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| Main Authors: | , , , |
| Format: | Article |
| Language: | English |
| Published: |
ELSEVIER
2024
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| Subjects: | |
| Online Access: | https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001216508000001 |