FKMAWCW: Categorical Fuzzy k-Modes Clustering with Automated Attribute-weight and Cluster-weight Learning
The Source_Code.rar file includes the MATLAB implementation of the FKMAWCW algorithm presented in: A. Golzari Oskouei, M. A. Balafar, and C. Motamed, "FKMAWCW: Categorical fuzzy k-modes clustering with automated attribute-weight and cluster-weight learning," Chaos, Solitons & Fractals, vol. 153, p. 111494, 2021/12/01/ 2021, doi: https://doi.org/10.1016/j.chaos.2021.111494.
Comments are written for all steps of the algorithm for better understanding the code. Also, a demo is implemented for ease of running, which runs by importing the data and other necessary algorithm parameters.
- Please cite the following papers:
[1] A. Golzari Oskouei, M. A. Balafar, and C. Motamed, "FKMAWCW: Categorical fuzzy k-modes clustering with automated attribute-weight and cluster-weight learning," Chaos, Solitons & Fractals, vol. 153, p. 111494, 2021/12/01/ 2021, doi: https://doi.org/10.1016/j.chaos.2021.111494.
[2] M. Hashemzadeh, A. Golzari Oskouei, and N. Farajzadeh, "New fuzzy C-means clustering method based on feature-weight and cluster-weight learning," Applied Soft Computing, vol. 78, pp. 324-345, 2019/05/01/ 2019, doi: https://doi.org/10.1016/j.asoc.2019.02.038.2
- Please do not distribute the dataset or source codes to others without the authorization from Dr. Amin Golzari Oskouei (first Author).
Author’ Email: a.golzari[at]tabrizu.ac.ir (A. Golzari Oskouei).