Genetic Algorithm for Feature Selection

Version 1.3 (59.7 KB) by Jingwei Too
Simple algorithm shows how the genetic algorithm (GA) used in the feature selection problem.


Updated 19 Dec 2020

From GitHub

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Simple genetic algorithm (GA) for feature selection tasks, which can select the potential features to improve the classification accuracy.

The < Main.m file > illustrates the example of how GA can solve the feature selection problem using a benchmark data-set.


Cite As

Too, Jingwei, and Abdul Rahim Abdullah. “A New and Fast Rival Genetic Algorithm for Feature Selection.” The Journal of Supercomputing, Springer Science and Business Media LLC, July 2020, doi:10.1007/s11227-020-03378-9.

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Too, Jingwei, et al. “EMG Feature Selection and Classification Using a Pbest-Guide Binary Particle Swarm Optimization.” Computation, vol. 7, no. 1, MDPI AG, Feb. 2019, p. 12, doi:10.3390/computation7010012.

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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

See release notes for this release on GitHub:


Solve one bug in the fitness function


Improve code for the fitness function


change to hold-out


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.