Genetic Algorithm for Feature Selection

Version 1.3 (62,1 KB) von Jingwei Too

Simple algorithm shows how the genetic algorithm (GA) used in the feature selection problem.

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

Verfolgen

0.0

(0)

1K Downloads

Aktualisiert 19. Dez 2020

Lizenz auf GitHub anzeigen

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.

**********************************************************************************************************************************

Zitieren als

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.

Mehrere Stile anzeigen

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.

Mehrere Stile anzeigen

Kompatibilität der MATLAB-Version

Erstellt mit R2018a

Kompatibel mit allen Versionen

Plattform-Kompatibilität

Windows macOS Linux

Tags Tags hinzufügen

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Version	Veröffentlicht	Versionshinweise
1.3	19. Dez 2020	See release notes for this release on GitHub: https://github.com/JingweiToo/Genetic-Algorithm-for-Feature-Selection/releases/tag/1.3	Herunterladen
1.2.1	22. Okt 2020	Solve one bug in the fitness function	Herunterladen
1.2	22. Okt 2020	Improve code for the fitness function	Herunterladen
1.1.0	23. Jul 2020	change to hold-out	Herunterladen
1.0.0	22. Jul 2020		Herunterladen

Um Probleme in diesem GitHub Add-On anzuzeigen oder zu melden, besuchen Sie das GitHub Repository.

MLA	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.
APA	Too, J., & Abdullah, A. R. (2020). A new and fast rival genetic algorithm for feature selection. The Journal of Supercomputing. Springer Science and Business Media LLC. Retrieved from https://doi.org/10.1007%2Fs11227-020-03378-9
BibTeX	@article{Too_2020, doi = {10.1007/s11227-020-03378-9}, url = {https://doi.org/10.1007%2Fs11227-020-03378-9}, year = 2020, month = {jul}, publisher = {Springer Science and Business Media {LLC}}, author = {Jingwei Too and Abdul Rahim Abdullah}, title = {A new and fast rival genetic algorithm for feature selection}, journal = {The Journal of Supercomputing} }

MLA	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.
APA	Too, J., Abdullah, A., Saad, N. M., & Tee, W. (2019). EMG Feature Selection and Classification Using a Pbest-Guide Binary Particle Swarm Optimization. Computation, 7(1), 12. MDPI AG. Retrieved from https://doi.org/10.3390%2Fcomputation7010012
BibTeX	@article{Too_2019, doi = {10.3390/computation7010012}, url = {https://doi.org/10.3390%2Fcomputation7010012}, year = 2019, month = {feb}, publisher = {{MDPI} {AG}}, volume = {7}, number = {1}, pages = {12}, author = {Jingwei Too and Abdul Abdullah and Norhashimah Mohd Saad and Weihown Tee}, title = {{EMG} Feature Selection and Classification Using a Pbest-Guide Binary Particle Swarm Optimization}, journal = {Computation} }