Amin-Golzari-Oskouei/SSFCM-FWCW

Feature-weight and Cluster-weight learning in Fuzzy C-Means method for Semi-Supervised Clustering

Feature-weight and Cluster-weight learning in Fuzzy C-Means method for Semi-Supervised Clustering

This repository includes the MATLAB implementation of the SSFCM-FWCW algorithm presented in:

Amin Golzari Oskouei, Negin Samadi, and Jafar Tanha, "Feature-weight and Cluster-weight learning in Fuzzy C-Means method for Semi-Supervised Clustering," Applied Soft Computing (submitted).

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] Amin Golzari Oskouei, Negin Samadi, and Jafar Tanha, "Feature-weight and Cluster-weight learning in Fuzzy C-Means method for Semi-Supervised Clustering," Applied Soft Computing (submitted).

[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).