@inproceedings{fbd307636e184c8c80c32419dda580c2,
title = "POCS-based Clustering Algorithm",
abstract = "A novel clustering technique based on the projection onto convex set (POCS) method, called POCS-based clustering algorithm, is proposed in this paper. The proposed POCS-based clustering algorithm exploits a parallel projection method of POCS to find appropriate cluster prototypes in the feature space. The algorithm considers each data point as a convex set and projects the cluster prototypes parallelly to the member data points. The projections are convexly combined to minimize the objective function for data clustering purpose. The performance of the proposed POCS-based clustering algorithm is verified through experiments on various synthetic datasets. The experimental results show that the proposed POCS-based clustering algorithm is competitive and efficient in terms of clustering error and execution speed when compared with other conventional clustering methods including Fuzzy C-Means (FCM) and K-Means clustering algorithms.",
keywords = "K-Means, POCS, clustering, machine learning, unsupervised learning",
author = "Tran, {Le Anh} and Deberneh, {Henock M.} and Do, {Truong Dong} and Nguyen, {Thanh Dat} and Le, {My Ha} and Park, {Dong Chul}",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2nd International Workshop on Intelligent Systems, IWIS 2022 ; Conference date: 17-08-2022 Through 19-08-2022",
year = "2022",
month = aug,
doi = "10.1109/IWIS56333.2022.9920762",
language = "English (US)",
series = "Proceedings - IWIS 2022: 2nd International Workshop on Intelligent Systems",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "Proceedings - IWIS 2022",
}