Embedded feature fusion for multi-label criteria selection via local search strategy and particle swarm optimization

Embedded feature fusion for multi-label criteria selection via local search strategy and particle swarm optimization

Abstract Multi-label classification is a significant challenge in machine learning, especially as the dimensionality of the problem increases. As the number of dimensions grows, the performance of traditional classification algorithms often degrades substantially. Feature selection is a key techniqu...

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Bibliographic Details
Main Authors: Suhua Chen, Xu Fang, Feng Zhai, Li Wang, Lin Lv
Format: Article
Language:English
Published: Nature Portfolio 2025-05-01
Series:Scientific Reports
Subjects:
Multi-label classification
Filter type
Local search strategy
Feature fusion
Collective intelligence
PSO algorithm
Online Access:https://doi.org/10.1038/s41598-025-01092-1
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https://doi.org/10.1038/s41598-025-01092-1

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