Binary Dragonfly Algorithm for Feature Selection

Version 1.1 (61.6 KB) by Jingwei Too
Application of Binary Dragonfly Algorithm (BDA) in the feature selection tasks.
4.0
(1)
409 Downloads
Updated 20 Dec 2020
View License on GitHub

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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Cite As

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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MATLAB Release Compatibility
Created with R2018a
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes
1.1

See release notes for this release on GitHub: https://github.com/JingweiToo/Binary-Dragonfly-Algorithm-for-Feature-Selection/releases/tag/1.1
1.0.1

Simplify the algorithm as hold-out
1.0.0

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.