Exploring Ant Colony Optimization for Feature Selection: A Comprehensive Review-Reference-Cited by-同舟云学术

Exploring Ant Colony Optimization for Feature Selection: A Comprehensive Review

Published:2024 Issue: Volume: Page:45-60
ISSN:2524-552X
Container-title:Springer Tracts in Nature-Inspired Computing
language:en
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Author:

Hashemi A.,Dowlatshahi M. B.

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-99-7227-2_3

Reference48 articles.

1. Dhal P, Azad C (2022) A comprehensive survey on feature selection in the various fields of machine learning. Appl Intell 52:4543–4581. https://doi.org/10.1007/s10489-021-02550-9

2. Jia W, Sun M, Lian J, Hou S (2022) Feature dimensionality reduction: a review. Complex Intell Syst 8:2663–2693. https://doi.org/10.1007/s40747-021-00637-x

3. Hashemi A, Dowlatshahi MB, Nezamabadi-pour H (2021) Minimum redundancy maximum relevance ensemble feature selection: a bi-objective Pareto-based approach. J Soft Comput Inf Technol

4. Bayati H, Dowlatshahi MB, Hashemi A (2022) MSSL: a memetic-based sparse subspace learning algorithm for multi-label classification. Int J Mach Learn Cyber 13:3607–3624. https://doi.org/10.1007/s13042-022-01616-5

5. Miri M, Dowlatshahi MB, Hashemi A et al (2022) Ensemble feature selection for multi-label text classification: an intelligent order statistics approach. Int J Intell Syst 37:11319–11341. https://doi.org/10.1002/int.23044

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