Some Clustering Methods, Algorithms and their Applications

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Before Cluster After Cluster
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Published: Jun 12, 2023
DOI: https://doi.org/10.17762/ijritcc.v11i6s.6946
Keywords:
Clustering, Partitioning Clustering, Hierarchical Clustering, Density-based Clustering, Grid-based Clustering, Fuzzy Clustering

Main Article Content

S. Velunachiyar
Research Scholar, Department of mathematics, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha University, Chennai, Tamilnadu-602105.
K. Sivakumar
Professor, Department of Mathematics, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha University, Chennai, Tamilnadu-602105.

Abstract

Clustering is a type of unsupervised learning [15]. When no target values are known, or "supervisors," in an unsupervised learning task, the purpose is to produce training data from the inputs themselves. Data mining and machine learning would be useless without clustering. If you utilize it to categorize your datasets according to their similarities, you'll be able to predict user behavior more accurately. The purpose of this research is to compare and contrast three widely-used data-clustering methods. Clustering techniques include partitioning, hierarchy, density, grid, and fuzzy clustering. Machine learning, data mining, pattern recognition, image analysis, and bioinformatics are just a few of the many fields where clustering is utilized as an analytical technique. In addition to defining the various algorithms, specialized forms of cluster analysis, linking methods, and please offer a review of the clustering techniques used in the big data setting.

Article Details

How to Cite
Velunachiyar, S. ., & Sivakumar, K. . (2023). Some Clustering Methods, Algorithms and their Applications. International Journal on Recent and Innovation Trends in Computing and Communication, 11(6s), 401–410. https://doi.org/10.17762/ijritcc.v11i6s.6946
Issue
Vol. 11 No. 6s (2023): Advances in Computational Modeling and Simulation of Computing Systems
Section
Articles

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