scarecrow777 / fkmawcw

FKMAWCW: Categorical Fuzzy k-Modes Clustering with Automated Attribute-weight and Cluster-weight Learning

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.

Condition and terms to use any sources of this project (Codes, Datasets, etc.):

1. 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

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).