Dynamic Multi-Level Competition Learning-Based Dual-Task Optimization for High-Dimensional Feature Selection

Feature selection (FS) is a critical task in data science and machine learning, presenting significant challenges in high-dimensional settings due to the complexity and noise inherent in large feature sets. To address these issues, this paper proposes a Dynamic Multi-Level Competition Learning-Based...

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發表在:	IEEE Access
Main Authors:	Weiwei Zhang, Yiwei Zhao, Chunbo Yuan, Xiaolong Chen, Wenzhao Liu, Yingjie Feng, Yongxin Feng, Jinchu Yang, Meng Li
格式:	Article
語言:	英语
出版:	IEEE 2024-01-01
主題:	Feature selection (FS) high-dimensional fisher score competitive swarm optimization (CSO)
在線閱讀:	https://ieeexplore.ieee.org/document/10776776/