Binary Dragonfly Algorithm for Feature Selection

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

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

Version 1.1 (61.6 KB)
431 Downloads
(1)
20 Dec 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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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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General Information

MATLAB Release Compatibility

  • 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.