Investigation of the performance of some clustering algorithms

Abstract In this dissertation, we investigate the performance of K-means, SOM and EM clustering algorithms based on UCI datasets. Tests are performed using three datasets. Two measures which are mostly used for comparing the performance of clustering algorithms. The first concerns the quality of clu...

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Main Author:	Tin Zar Kyaw.
Other Authors:	School of Electrical and Electronic Engineering
Format:	Theses and Dissertations
Published:	2008
Subjects:	DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
Online Access:	http://hdl.handle.net/10356/3602
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Institution:	Nanyang Technological University

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spelling	sg-ntu-dr.10356-36022023-07-04T15:17:23Z Investigation of the performance of some clustering algorithms Tin Zar Kyaw. School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems Abstract In this dissertation, we investigate the performance of K-means, SOM and EM clustering algorithms based on UCI datasets. Tests are performed using three datasets. Two measures which are mostly used for comparing the performance of clustering algorithms. The first concerns the quality of clustering algorithms. The second measure deals with the accuracy of clustering results. The results of the experiments suggest that Expectation Maximization (EM) is more robust to outliners than K-means and SOM. Master of Science (Consumer Electronics) 2008-09-17T09:33:17Z 2008-09-17T09:33:17Z 2005 2005 Thesis http://hdl.handle.net/10356/3602 Nanyang Technological University application/pdf
institution	Nanyang Technological University
building	NTU Library
continent	Asia
country	Singapore Singapore
content_provider	NTU Library
collection	DR-NTU
topic	DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
spellingShingle	DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems Tin Zar Kyaw. Investigation of the performance of some clustering algorithms
description	Abstract In this dissertation, we investigate the performance of K-means, SOM and EM clustering algorithms based on UCI datasets. Tests are performed using three datasets. Two measures which are mostly used for comparing the performance of clustering algorithms. The first concerns the quality of clustering algorithms. The second measure deals with the accuracy of clustering results. The results of the experiments suggest that Expectation Maximization (EM) is more robust to outliners than K-means and SOM.
author2	School of Electrical and Electronic Engineering
author_facet	School of Electrical and Electronic Engineering Tin Zar Kyaw.
format	Theses and Dissertations
author	Tin Zar Kyaw.
author_sort	Tin Zar Kyaw.
title	Investigation of the performance of some clustering algorithms
title_short	Investigation of the performance of some clustering algorithms
title_full	Investigation of the performance of some clustering algorithms
title_fullStr	Investigation of the performance of some clustering algorithms
title_full_unstemmed	Investigation of the performance of some clustering algorithms
title_sort	investigation of the performance of some clustering algorithms
publishDate	2008
url	http://hdl.handle.net/10356/3602
_version_	1772826201028558848

Investigation of the performance of some clustering algorithms

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