A matlab implementation of paper "Unsupervised multi-view fuzzy c-means clustering algorithm."
Published in Electronics'24
We propose a novel MV-FCM clustering algorithm with an unsupervised learning framework, called the unsupervised MV-FCM (U-MV-FCM), such that it can search an optimal number of clusters during the iteration process of the algorithm without giving the number of clusters a priori. It is also free of initializations and parameter selection. We then use three synthetic and six benchmark datasets to make comparisons between the proposed U- MV-FCM and other existing algorithms and to highlight its practical implications.
In case the repository or the publication was helpful in your work, please use the following to cite the original paper,
@article{hussain2023unsupervised,
title={Unsupervised multiview fuzzy c-means clustering algorithm},
author={Hussain, Ishtiaq and Sinaga, Kristina P and Yang, Miin-Shen},
journal={Electronics},
volume={12},
number={21},
pages={4467},
year={2023},
publisher={MDPI}
}