Binary Dragonfly Algorithm for Feature Selection

Version 1.1 (61,6 KB) von 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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Aktualisiert 20. Dez 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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Zitieren als

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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Erstellt mit R2018a

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Version	Veröffentlicht	Versionshinweise
1.1	20. Dez 2020	See release notes for this release on GitHub: https://github.com/JingweiToo/Binary-Dragonfly-Algorithm-for-Feature-Selection/releases/tag/1.1	Herunterladen
1.0.1	9. Nov 2020	Simplify the algorithm as hold-out	Herunterladen
1.0.0	22. Okt 2020		Herunterladen

Um Probleme in diesem GitHub Add-On anzuzeigen oder zu melden, besuchen Sie das 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} }