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Binary Grey Wolf Optimization for Feature Selection

version 1.3 (59.6 KB) by Jingwei Too
Demonstration on how binary grey wolf optimization (BGWO) applied in the feature selection task.

968 Downloads

Updated 19 Dec 2020

From GitHub

View license on GitHub

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.

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

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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.