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MEL: Efficient Multi-Task Evolutionary Learning for High-Dimensional Feature Selection
Feb. 15, 2024, 5:41 a.m. | Xubin Wang, Haojiong Shangguan, Fengyi Huang, Shangrui Wu, Weijia Jia
cs.LG updates on arXiv.org arxiv.org
Abstract: Feature selection is a crucial step in data mining to enhance model performance by reducing data dimensionality. However, the increasing dimensionality of collected data exacerbates the challenge known as the "curse of dimensionality", where computation grows exponentially with the number of dimensions. To tackle this issue, evolutionary computational (EC) approaches have gained popularity due to their simplicity and applicability. Unfortunately, the diverse designs of EC methods result in varying abilities to handle different data, often …
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