A Study on the Clustering Techniques and Performance Evaluation:

F. Mohamed Ilyas The New College, India https://orcid.org/0009-0002-8954-2449 S. Silvia Priscila Bharath Institute of Higher Education and Research, India https://orcid.org/0000-0002-6040-3149 V. Poornima Vels Institute of Science, Technology, and Advanced Studies, India Prasanna Ranjith Christodoss Messiah University, USA D. Kerana Hanirex Bharath Institute of Higher Education and Research, India C. Elayaraja Dhaanish Ahmed College of Engineering, India M. Sakthivanitha Vels Institute of Science, Technology, and Advanced Studies, India https://orcid.org/0009-0001-6795-6555 A. T. Ashmi Christus Dhaanish Ahmed College of Engineering, India A Study on the Clustering Techniques and Performance Evaluation

People prefer approximations based on resemblance, particularly when dealing with commercial figures. With data, the procedure is even more exact, known as Clustering. Clustering is a method that has numerous applications. Numerous fields, including pattern identification, image analysis, consumer statistical analysis, segmentation of markets, social network analysis, and more, use clustering, an unsupervised machine learning technique. It can effectively address many problems and goals, from the most basic to the most complicated. Cluster analysis is an effective approach for detecting underlying structures and patterns in data from diverse areas. It divides the data into clusters based on their similarities or differences. Researchers and analysts can get significant insights and make data-based decisions by combining comparable observations. Further, Clustering on the original information provided us with extremely valuable and unique explanations for each of the individual segments.
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