Computer Department, Makhanlal Chaturvedi National University of Journalism and Communication, India
Email: urvashikushsoni2016@gmail.co (U.S.); ddwivedi2001@gmail.com (S.D.)
*Corresponding author
Manuscript received December 12, 2023; revised January 12, 2024; accepted January 30, 2024; published February 29, 2024
Abstract—The success of clustering depends critically on a number of key concerns, one of which is clustering validation. In general, there are three types of clustering validation criteria: relative clustering validation, internal clustering validation, and external clustering validation. This paper focuses on the clustering validation criteria and provides a thorough analysis of the most popular clustering validation for crisp clustering. We investigate the validation properties over the five conventional clustering. According to experiment results, Silhouette is the validation measure that performs well in all five areas whereas other measures have some limits in various application.
Keywords—voting, consensus clustering, ensemble generation, co-occurrence matrices
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Cite: Urvashi Soni and Sunita Dwivedi, "Clutching of Clustering Validation Criteria,"
International Journal of Future Computer and Communication, vol. 13, no. 1, pp. 6-12, 2024.
Copyright © 2024 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
(CC BY 4.0)
