Enhancing Diversity in Multi-objective Feature Selection

Autor: Miyandoab, Sevil Zanjani, Rahnamayan, Shahryar, Bidgoli, Azam Asilian, Ebrahimi, Sevda, Makrehchi, Masoud

Publikováno v: S. Z. Miyandoab, S. Rahnamayan, A. A. Bidgoli, S. Ebrahimi, and M. Makrehchi, "Enhancing Diversity in Multi-Objective Feature Selection," 2024 IEEE Congress on Evolutionary Computation (CEC), Yokohama, Japan, 2024, pp. 1-8

Feature selection plays a pivotal role in the data preprocessing and model-building pipeline, significantly enhancing model performance, interpretability, and resource efficiency across diverse domains. In population-based optimization methods, the g

Externí odkaz: http://arxiv.org/abs/2407.17795