Binary Grey Wolf Optimization for Feature Selection
This toolbox offers two types of binary grey wolf optimization (BGWO) methods
The < Main.m file > demos the examples of how BGWO solves the feature selection problem using benchmark data-set.
**********************************************************************************************************************************
Please consider citing my article
[1] Too, Jingwei, et al. “A New Competitive Binary Grey Wolf Optimizer to Solve the Feature Selection Problem in EMG Signals Classification.” Computers, vol. 7, no. 4, MDPI AG, Nov. 2018, p. 58, DOI:https://doi.org/10.3390/computers7040058
[2] Too, Jingwei, and Abdul Rahim Abdullah. “Opposition Based Competitive Grey Wolf Optimizer for EMG Feature Selection.” Evolutionary Intelligence, Springer Science and Business Media LLC, July 2020, DOI: https://doi.org/10.1007/s12065-020-00441-5
MATLAB Release Compatibility
Platform Compatibility
Windows macOS LinuxCategories
- AI and Statistics > Statistics and Machine Learning Toolbox > Dimensionality Reduction and Feature Extraction >
Tags
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!Discover Live Editor
Create scripts with code, output, and formatted text in a single executable document.
Version | Published | Release Notes | |
---|---|---|---|
1.3 | See release notes for this release on GitHub: https://github.com/JingweiToo/Binary-Grey-Wolf-Optimization-for-Feature-Selection/releases/tag/1.3 |
||
1.2 | Improve code for the fitness function |
||
1.1.0 | Change to hold-out |
||
1.0.6 | - |
||
1.0.5 | - |
||
1.0.4 | - |
||
1.0.3 | Simplify BGWO1 program. |
||
1.0.2 | - |
||
1.0.1 | - |
||
1.0.0 |