Feature Selection for High-Dimensional Data Based on a Multi-objective Particle Swarm Optimization with Self-adjusting Strategy Pool

Author:

Peng YingyuORCID,Wang RuiqiORCID,Yu DandanORCID,Zhou YuORCID

Publisher

Springer Nature Singapore

Reference23 articles.

1. Xue, B., Zhang, M., Browne, W.N., Yao, X.: A survey on evolutionary computation approaches to feature selection. IEEE Trans. Evol. Comput. 20(4), 606–626 (2016)

2. Kira, K., Rendell, L.A.: The feature selection problem: traditional methods and a new algorithm. In: Proceedings of the Tenth National Conference on Artificial Intelligence, pp. 129–134 (1992)

3. Zhao, X., Liu, Z.: Hybrid particle swarm optimization with differential and perturbation. J. Front. Comput. Sci. Technol. 8(2), 218 (2014)

4. Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence);HB Nguyen,2016

5. Xue, B., Cervante, L., Shang, L., Borowne, W.N., Zhang, M.J.: Multi-objective evolutionary algorithms for filter based feature selection in classification. Int. J. Artif. Intell. Tools 22(4), 1–34 (2013)

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