Binary Particle Swarm Optimization for Feature Selection

Versione 1.3 (61,2 KB) da Jingwei Too

Simple algorithm shows how binary particle swarm optimization (BPSO) used in feature selection problem.

https://github.com/JingweiToo/Binary-Particle-Swarm-Optimization-for-Feature-Selection

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Aggiornato 19 dic 2020

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Simple binary particle swarm optimization (BPSO) for feature selection tasks, which can select the potential features to improve the classification accuracy.

The < Main.m file > demos an example on how to use BPSO with classification error rate (computed by KNN) as the fitness function for feature selection problem using benchmark data-set.

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Cita come

Too, Jingwei, et al. “A New Co-Evolution Binary Particle Swarm Optimization with Multiple Inertia Weight Strategy for Feature Selection.” Informatics, vol. 6, no. 2, MDPI AG, May 2019, p. 21, doi:10.3390/informatics6020021.

Visualizza più stili

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.

Visualizza più stili

Compatibilità della release di MATLAB

Creato con R2018a

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Categorie

Mathematics and Optimization > Global Optimization Toolbox > Particle Swarm >

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Versione	Pubblicato	Note della release
1.3	19 dic 2020	See release notes for this release on GitHub: https://github.com/JingweiToo/Binary-Particle-Swarm-Optimization-for-Feature-Selection/releases/tag/1.3	Scarica
1.2	22 ott 2020	Improve code for the fitness function	Scarica
1.1.0	23 lug 2020	change to hold-out	Scarica
1.0.4	22 lug 2020	-	Scarica
1.0.3	30 giu 2019	Changes Vmin=-Vmax	Scarica
1.0.2	8 mag 2019	-	Scarica
1.0.1	8 mag 2019	Add convergence plot	Scarica
1.0.0	7 mag 2019		Scarica

Per visualizzare o segnalare problemi su questo componente aggiuntivo di GitHub, visita GitHub Repository.

MLA	Too, Jingwei, et al. “A New Co-Evolution Binary Particle Swarm Optimization with Multiple Inertia Weight Strategy for Feature Selection.” Informatics, vol. 6, no. 2, MDPI AG, May 2019, p. 21, doi:10.3390/informatics6020021.
APA	Too, J., Abdullah, A. R., & Saad, N. M. (2019). A New Co-Evolution Binary Particle Swarm Optimization with Multiple Inertia Weight Strategy for Feature Selection. Informatics, 6(2), 21. MDPI AG. Retrieved from https://doi.org/10.3390%2Finformatics6020021
BibTeX	@article{Too_2019, doi = {10.3390/informatics6020021}, url = {https://doi.org/10.3390%2Finformatics6020021}, year = 2019, month = {may}, publisher = {{MDPI} {AG}}, volume = {6}, number = {2}, pages = {21}, author = {Jingwei Too and Abdul Rahim Abdullah and Norhashimah Mohd Saad}, title = {A New Co-Evolution Binary Particle Swarm Optimization with Multiple Inertia Weight Strategy for Feature Selection}, journal = {Informatics} }

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} }