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A Comparative Analysis of Clustering Algorithms

by Raj Bala, Sunil Sikka, Juhi Singh
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 100 - Number 15
Year of Publication: 2014
Authors: Raj Bala, Sunil Sikka, Juhi Singh
10.5120/17603-8293

Raj Bala, Sunil Sikka, Juhi Singh . A Comparative Analysis of Clustering Algorithms. International Journal of Computer Applications. 100, 15 ( August 2014), 35-39. DOI=10.5120/17603-8293

@article{ 10.5120/17603-8293,
author = { Raj Bala, Sunil Sikka, Juhi Singh },
title = { A Comparative Analysis of Clustering Algorithms },
journal = { International Journal of Computer Applications },
issue_date = { August 2014 },
volume = { 100 },
number = { 15 },
month = { August },
year = { 2014 },
issn = { 0975-8887 },
pages = { 35-39 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume100/number15/17603-8293/ },
doi = { 10.5120/17603-8293 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:30:04.184859+05:30
%A Raj Bala
%A Sunil Sikka
%A Juhi Singh
%T A Comparative Analysis of Clustering Algorithms
%J International Journal of Computer Applications
%@ 0975-8887
%V 100
%N 15
%P 35-39
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Clustering is a process of grouping a set of similar data objects within the same group based on similarity criteria (i. e. based on a set of attributes). There are many clustering algorithms. The objective of this paper is to perform a comparative analysis of four clustering algorithms namely K-means algorithm, Hierarchical algorithm, Expectation and maximization algorithm and Density based algorithm. These algorithms are compared in terms of efficiency and accuracy, using WEKA tool. The data for clustering is used in normalized and as well as unnormalized format. In terms of efficiency and accuracy K-means produces better results as compared to other algorithms.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Clustering K-means algorithm Hierarchical algorithm Expectation and maximization algorithm and Density based algorithm and WEKA tool.

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