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Cluster Analysis: Preliminaries and Techniques

by Tejas Karangale, Shalmali Bhoir
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 129 - Number 14
Year of Publication: 2015
Authors: Tejas Karangale, Shalmali Bhoir
10.5120/ijca2015907104

Tejas Karangale, Shalmali Bhoir . Cluster Analysis: Preliminaries and Techniques. International Journal of Computer Applications. 129, 14 ( November 2015), 36-40. DOI=10.5120/ijca2015907104

@article{ 10.5120/ijca2015907104,
author = { Tejas Karangale, Shalmali Bhoir },
title = { Cluster Analysis: Preliminaries and Techniques },
journal = { International Journal of Computer Applications },
issue_date = { November 2015 },
volume = { 129 },
number = { 14 },
month = { November },
year = { 2015 },
issn = { 0975-8887 },
pages = { 36-40 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume129/number14/23144-2015907104/ },
doi = { 10.5120/ijca2015907104 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:23:26.986004+05:30
%A Tejas Karangale
%A Shalmali Bhoir
%T Cluster Analysis: Preliminaries and Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 129
%N 14
%P 36-40
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Clustering is one of the most useful tasks in data mining process for discovering groups and identifying interesting patterns in the underlying data. Cluster analysis is a widely used technique today in fields like Healthcare, Sociology and Biology etc. to identify the patterns from a huge amount of data. It has many applications such as image segmentation, information retrieval, web pages grouping, market segmentation, and scientific and engineering analysis. This paper gives an overview of cluster analysis. It describes all the preliminaries required for the process and cites the main algorithms of clustering with their pros and cons.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Clustering algorithms Cluster Analysis Hierarchical clustering Partitional Clustering.

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