Genetic Algorithm for Feature Selection
Simple algorithm shows how the genetic algorithm (GA) used in the feature selection problem.
https://github.com/JingweiToo/Genetic-Algorithm-for-Feature-Selection
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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.
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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.
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.
General Information
- Version 1.3 (62.1 KB)
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View License on GitHub
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
| Version | Published | Release Notes | Action |
|---|---|---|---|
| 1.3 | See release notes for this release on GitHub: https://github.com/JingweiToo/Genetic-Algorithm-for-Feature-Selection/releases/tag/1.3 |
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| 1.2.1 | Solve one bug in the fitness function |
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| 1.2 | Improve code for the fitness function |
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| 1.1.0 | change to hold-out |
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| 1.0.0 |
