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Reseach Article

Comparative Study and Performance Analysis of Clustering Algorithms

Published on April 2016 by Kamalpreet Kaur Jassar, Kanwalvir Singh Dhindsa
International Conference on ICT for Healthcare
Foundation of Computer Science USA
ICTHC2015 - Number 1
April 2016
Authors: Kamalpreet Kaur Jassar, Kanwalvir Singh Dhindsa

Kamalpreet Kaur Jassar, Kanwalvir Singh Dhindsa . Comparative Study and Performance Analysis of Clustering Algorithms. International Conference on ICT for Healthcare. ICTHC2015, 1 (April 2016), 1-6.

author = { Kamalpreet Kaur Jassar, Kanwalvir Singh Dhindsa },
title = { Comparative Study and Performance Analysis of Clustering Algorithms },
journal = { International Conference on ICT for Healthcare },
issue_date = { April 2016 },
volume = { ICTHC2015 },
number = { 1 },
month = { April },
year = { 2016 },
issn = 0975-8887,
pages = { 1-6 },
numpages = 6,
url = { /proceedings/icthc2015/number1/24651-8249/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Proceeding Article
%1 International Conference on ICT for Healthcare
%A Kamalpreet Kaur Jassar
%A Kanwalvir Singh Dhindsa
%T Comparative Study and Performance Analysis of Clustering Algorithms
%J International Conference on ICT for Healthcare
%@ 0975-8887
%V ICTHC2015
%N 1
%P 1-6
%D 2016
%I International Journal of Computer Applications

Spatial clustering is a process of grouping a set of spatial objects into groups, these groups are called clusters. Objects within a one cluster show a high degree of similarity, whereas the objects in another cluster are as much non-similar as possible. Clustering is a very well known technique of data mining which is mostly used method of analyzing and describing the data. It is one of the techniques to deal with the large geographical datasets. Clustering is the mostly used method of data mining. SOM and k-means are two classical methods for clustering. This paper illustrates the approach of clustering: Kohonen SOM and K-Means have been discussed and compared using different parameters on same dataset. After comparing these methods effectively, results of the experiments suggest that Self-Organizing Maps (SOM) is more robust to outlier than the k-means method. In this paper, experiments have been performed to compare the performances of clustering algorithms.

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Index Terms

Computer Science
Information Sciences


Spatial Clustering Clustering Algorithms Som K-means Pca Etc.