JCIF Feature Selection Method

Version 1.0.0 (6,01 ko) par U A Md Ehsan

This function implements the JCIF feature selection method

Suivre

0.0

(0)

2 téléchargements

Mise à jour 24 déc. 2025

Afficher la licence

This repository provides a MATLAB implementation of the Joint Conditional Mutual Information for Selecting Informative Feature (JCIF) selection criterion for supervised feature selection.

JCIF is an information-theoretic method that incrementally selects features by jointly considering:

Redundency handled using conditional mutual information, and Relevence via joint mutual information.

The method is designed for discrete-valued data and is particularly suitable for high-dimensional feature spaces.

Citation pour cette source

Ali, U. A. Md Ehsan, and Keisuke Kameyama. “Informative Band Subset Selection for Hyperspectral Image Classification Using Joint and Conditional Mutual Information.” 2022 IEEE Symposium Series on Computational Intelligence (SSCI), IEEE, 2022, pp. 573–80, https://doi.org/10.1109/ssci51031.2022.10022154.

Afficher d’autres styles

Compatibilité avec les versions de MATLAB

Créé avec R2025b

Compatible avec toutes les versions

Plateformes compatibles

Windows macOS Linux

Tags Ajouter des tags

Community Treasure Hunt

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

Start Hunting!

Version	Publié le	Notes de version
1.0.0	24 déc. 2025		Télécharger

MLA	Ali, U. A. Md Ehsan, and Keisuke Kameyama. “Informative Band Subset Selection for Hyperspectral Image Classification Using Joint and Conditional Mutual Information.” 2022 IEEE Symposium Series on Computational Intelligence (SSCI), IEEE, 2022, pp. 573–80, https://doi.org/10.1109/ssci51031.2022.10022154.
APA	Ali, U. A. M. E., & Kameyama, K. (2022). Informative Band Subset Selection for Hyperspectral Image Classification using Joint and Conditional Mutual Information. In 2022 IEEE Symposium Series on Computational Intelligence (SSCI) (pp. 573–580). IEEE. Retrieved from http://dx.doi.org/10.1109/SSCI51031.2022.10022154
BibTeX	@inproceedings{Ali_2022, title={Informative Band Subset Selection for Hyperspectral Image Classification using Joint and Conditional Mutual Information}, url={http://dx.doi.org/10.1109/SSCI51031.2022.10022154}, DOI={10.1109/ssci51031.2022.10022154}, booktitle={2022 IEEE Symposium Series on Computational Intelligence (SSCI)}, publisher={IEEE}, author={Ali, U A Md Ehsan and Kameyama, Keisuke}, year={2022}, month=dec, pages={573–580} }