Empirical Analysis on the Efficiency of Clustering Algorithms Based on the Significance of Cluster Size

  • Sunitha Cheriyan Higher College of Technology Muscat, Sultanate of Oman
  • Shaniba Ibrahim Higher College of Technology Muscat, Sultanate of Oman
  • Susan Treesa Higher College of Technology Muscat, Sultanate of Oman

Abstract

This paper mainly focuses on the performance of the various clustering algorithm on a particular dataset based on the number of clusters defined. The analysis is performed on the iris dataset from the dataset library. It also compares the performance of the algorithms based on the number of clusters defined. The various algorithms used for the comparison includes K-Means, Hierarchical, Model based and Density based Clustering based on Statistical models.


DOI:https://doi.org/10.6025/jdim/2023/21/1/9-17


 

Published
2023-03-01
How to Cite
CHERIYAN, Sunitha; IBRAHIM, Shaniba; TREESA, Susan. Empirical Analysis on the Efficiency of Clustering Algorithms Based on the Significance of Cluster Size. Journal of Digital Information Management(JDIM), [S.l.], v. 21, n. 1, p. 9-17, mar. 2023. ISSN 0972-7272. Available at: <https://www.dline.info/ojs/index.php/jdim/article/view/22>. Date accessed: 21 apr. 2026.
Citation Formats
Issue
Vol 21 No 1 (2023): Volume 21 Number 1 March 2023
Section
Research