@misc{10481/72141,
year = {2021},
month = {4},
url = {http://hdl.handle.net/10481/72141},
abstract = {The size of data that we generate every day across the globe is undoubtedly astonishing due to the growth
of the Internet of Things. So, it is a common practice to unravel important hidden facts and understand the
massive data using clustering techniques. However, non- linear relations, which are essentially unexplored
when compared to linear correlations, are more widespread within data that is high throughput. Often, nonlinear
links can model a large amount of data in a more precise fashion and highlight critical trends and
patterns. Moreover, selecting an appropriate measure of similarity is a well-known issue since many years
when it comes to data clustering. In this work, a non-Euclidean similarity measure is proposed, which relies on
non-linear Jeffreys-divergence (JS). We subsequently develop c- means using the proposed JS (J-c-means). The
various properties of the JS and J-c-means are discussed. All the analyses were carried out on a few real-life
and synthetic databases. The obtained outcomes show that J-c-means outperforms some cutting-edge c-means
algorithms empirically.},
organization = {project "Prediction of diseases through computer assisted diagnosis system using images captured by minimally-invasive and non-invasive modalities", Computer Science and Engineering, PDPM Indian Institute of Information Technology, Design and Manufacturing	SPARC-MHRD-231},
organization = {project Grant Agency of Excellence, University of Hradec Kralove, Faculty of Informatics and Management, Czech Republic	UHK-FIM-GE-2204-2021},
publisher = {Universidad Internacional de La Rioja},
keywords = {C-mean},
keywords = {Clustering},
keywords = {Convergence},
keywords = {Jeffreys-Divergence},
keywords = {Jeffreys-Similarity Measure},
title = {Performance and Convergence Analysis of Modified C-Means Using Jeffreys-Divergence for Clustering},
doi = {10.9781/ijimai.2021.04.009},
author = {Seal, Ayan and Herrera Viedma, Enrique},
}