Binary Dragonfly Algorithm for Feature Selection

Versione 1.1 (61,6 KB) da Jingwei Too

Application of Binary Dragonfly Algorithm (BDA) in the feature selection tasks.

https://github.com/JingweiToo/Binary-Dragonfly-Algorithm-for-Feature-Selection

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Aggiornato 20 dic 2020

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This toolbox offers a Binary Dragonfly Algorithm (BDA) method

The < Main.m file > illustrates the example of how BDA can solve the feature selection problem using benchmark data-set.

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Cita come

Too, Jingwei, and Seyedali Mirjalili. “A Hyper Learning Binary Dragonfly Algorithm for Feature Selection: A COVID-19 Case Study.” Knowledge-Based Systems, vol. 212, Elsevier BV, Jan. 2021, p. 106553, doi:10.1016/j.knosys.2020.106553.

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Versione	Pubblicato	Note della release
1.1	20 dic 2020	See release notes for this release on GitHub: https://github.com/JingweiToo/Binary-Dragonfly-Algorithm-for-Feature-Selection/releases/tag/1.1	Scarica
1.0.1	9 nov 2020	Simplify the algorithm as hold-out	Scarica
1.0.0	22 ott 2020		Scarica

Per visualizzare o segnalare problemi su questo componente aggiuntivo di GitHub, visita GitHub Repository.

MLA	Too, Jingwei, and Seyedali Mirjalili. “A Hyper Learning Binary Dragonfly Algorithm for Feature Selection: A COVID-19 Case Study.” Knowledge-Based Systems, vol. 212, Elsevier BV, Jan. 2021, p. 106553, doi:10.1016/j.knosys.2020.106553.
APA	Too, J., & Mirjalili, S. (2021). A Hyper Learning Binary Dragonfly Algorithm for Feature Selection: A COVID-19 Case Study. Knowledge-Based Systems, 212, 106553. Elsevier BV. Retrieved from https://doi.org/10.1016%2Fj.knosys.2020.106553
BibTeX	@article{Too_2021, doi = {10.1016/j.knosys.2020.106553}, url = {https://doi.org/10.1016%2Fj.knosys.2020.106553}, year = 2021, month = {jan}, publisher = {Elsevier {BV}}, volume = {212}, pages = {106553}, author = {Jingwei Too and Seyedali Mirjalili}, title = {A Hyper Learning Binary Dragonfly Algorithm for Feature Selection: A {COVID}-19 Case Study}, journal = {Knowledge-Based Systems} }