conference-paper

A Comparative Study of Clustering Algorithms

  • International Conference on Computing for Sustainable Global Development
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Abstract

In present era, data analysis plays vital role in various domains. Data clustering is a data analysis technique used for grouping of data objects based on unsupervised learning. Many clustering algorithms have been proposed in the literature. Each algorithm possesses some strengths and weaknesses. Therefore, a set of clustering algorithms are appropriate for one set of application area while another set of clustering algorithm are suitable for another set of application areas. In this paper, popular traditional algorithms are discussed. A comprehensive comparative study of different clustering algorithms is presented in this paper. These clustering algorithms are compared in detail based on various parameters used in these methods.

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Publication details

OpenAlex
W3006448378
Document type
conference-paper
Language
EN
Source
International Conference on Computing for Sustainable Global Development
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