Binary Dragonfly Algorithm for Feature Selection

版本 1.1 (61.6 KB) 作者: 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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4.0

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388.0 次下载

更新时间 2020/12/20

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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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引用格式

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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版本	已发布	发行说明
1.1	2020/12/20	See release notes for this release on GitHub: https://github.com/JingweiToo/Binary-Dragonfly-Algorithm-for-Feature-Selection/releases/tag/1.1	下载
1.0.1	2020/11/9	Simplify the algorithm as hold-out	下载
1.0.0	2020/10/22		下载

要查看或报告此来自 GitHub 的附加功能中的问题，请访问其 GitHub 仓库。

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} }

Binary Dragonfly Algorithm for Feature Selection