Datasets Size: Effect on Clustering Results

The recent advancement in the way we capture and store data pose a serious challenge for data analysis. This gives a wider acceptance to data mining, being an interdisciplinary field that implements algorithm on stored data with a view to discovering hidden knowledge. Most people that keep records,...

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Main Authors:	Raheem, Ajiboye Adeleke, Ruzaini, Abdullah Arshah, Hongwu, Qin
Format:	Conference or Workshop Item
Language:	English
Published:	2013
Subjects:	QA76 Computer software
Online Access:	http://umpir.ump.edu.my/id/eprint/5007/ http://umpir.ump.edu.my/id/eprint/5007/1/22-UMP.pdf

id	ump-5007
recordtype	eprints
spelling	ump-50072018-05-18T02:50:35Z http://umpir.ump.edu.my/id/eprint/5007/ Datasets Size: Effect on Clustering Results Raheem, Ajiboye Adeleke Ruzaini, Abdullah Arshah Hongwu, Qin QA76 Computer software The recent advancement in the way we capture and store data pose a serious challenge for data analysis. This gives a wider acceptance to data mining, being an interdisciplinary field that implements algorithm on stored data with a view to discovering hidden knowledge. Most people that keep records, however, are yet to reap the benefits of this tool, this is due to the general notion that a large datasets is required to guarantee reliable results. However, this may not be applicable in all cases. In this paper, we proposed a research technique that implements descriptive algorithms on numeric datasets of varied sizes. We modeled each subset of our data using EM clustering algorithm; two different numbers of partitions (k) were estimated and used for each experiment. The clustering results were validated using external evaluation measure in order to determine their level of correctness. The approach unveils the implication of datasets size on the clusters formed and the impact of estimated number of partitions. 2013-04-20 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/5007/1/22-UMP.pdf Raheem, Ajiboye Adeleke and Ruzaini, Abdullah Arshah and Hongwu, Qin (2013) Datasets Size: Effect on Clustering Results. In: 3rd International Conference on Software Engineering & Computer Systems (ICSECS - 2013), 20-22 Ogos 2013 , Universiti Malaysia Pahang. pp. 1-9.. (Unpublished)
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	QA76 Computer software
spellingShingle	QA76 Computer software Raheem, Ajiboye Adeleke Ruzaini, Abdullah Arshah Hongwu, Qin Datasets Size: Effect on Clustering Results
description	The recent advancement in the way we capture and store data pose a serious challenge for data analysis. This gives a wider acceptance to data mining, being an interdisciplinary field that implements algorithm on stored data with a view to discovering hidden knowledge. Most people that keep records, however, are yet to reap the benefits of this tool, this is due to the general notion that a large datasets is required to guarantee reliable results. However, this may not be applicable in all cases. In this paper, we proposed a research technique that implements descriptive algorithms on numeric datasets of varied sizes. We modeled each subset of our data using EM clustering algorithm; two different numbers of partitions (k) were estimated and used for each experiment. The clustering results were validated using external evaluation measure in order to determine their level of correctness. The approach unveils the implication of datasets size on the clusters formed and the impact of estimated number of partitions.
format	Conference or Workshop Item
author	Raheem, Ajiboye Adeleke Ruzaini, Abdullah Arshah Hongwu, Qin
author_facet	Raheem, Ajiboye Adeleke Ruzaini, Abdullah Arshah Hongwu, Qin
author_sort	Raheem, Ajiboye Adeleke
title	Datasets Size: Effect on Clustering Results
title_short	Datasets Size: Effect on Clustering Results
title_full	Datasets Size: Effect on Clustering Results
title_fullStr	Datasets Size: Effect on Clustering Results
title_full_unstemmed	Datasets Size: Effect on Clustering Results
title_sort	datasets size: effect on clustering results
publishDate	2013
url	http://umpir.ump.edu.my/id/eprint/5007/ http://umpir.ump.edu.my/id/eprint/5007/1/22-UMP.pdf
first_indexed	2023-09-18T22:00:05Z
last_indexed	2023-09-18T22:00:05Z
_version_	1777414340094197760

Datasets Size: Effect on Clustering Results

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