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Centre-based hard clustering algorithms for Y-STR data / Ali Seman, Zainab Abu Bakar and Azizian Mohd. Sapawi

This paper presents Centre-based hard clustering approaches for clustering Y-STR data. Two classical partitioning techniques: Centroid-based partitioning technique and Representative object-based partitioning technique are evaluated. The k-Means and the k-Modes algorithms are the fundamental algorit...

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Main Authors: Seman, Ali, Abu Bakar, Zainab, Mohd. Sapawi, Azizian
Format: Article
Language:English
Published: Faculty of Computer and Mathematical Sciences 2010
Online Access:https://ir.uitm.edu.my/id/eprint/11101/1/11101.pdf
https://ir.uitm.edu.my/id/eprint/11101/
https://mjoc.uitm.edu.my/
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spelling my.uitm.ir.111012022-06-14T02:32:24Z https://ir.uitm.edu.my/id/eprint/11101/ Centre-based hard clustering algorithms for Y-STR data / Ali Seman, Zainab Abu Bakar and Azizian Mohd. Sapawi Seman, Ali Abu Bakar, Zainab Mohd. Sapawi, Azizian This paper presents Centre-based hard clustering approaches for clustering Y-STR data. Two classical partitioning techniques: Centroid-based partitioning technique and Representative object-based partitioning technique are evaluated. The k-Means and the k-Modes algorithms are the fundamental algorithms for the centroid-based partitioning technique, whereas the k-Medoids is a representative object-based partitioning technique. The three algorithms above are experimented and evaluated in partitioning Y-STR haplogroups and Y-STR Surname data. The overall results show that the centroid-based partitioning technique is better than the representative object-based partitioning technique in clustering Y-STR data. Faculty of Computer and Mathematical Sciences 2010 Article PeerReviewed text en https://ir.uitm.edu.my/id/eprint/11101/1/11101.pdf Centre-based hard clustering algorithms for Y-STR data / Ali Seman, Zainab Abu Bakar and Azizian Mohd. Sapawi. (2010) Malaysian Journal of Computing (MJoC), 1 (1). pp. 62-73. ISSN 2231-7473 https://mjoc.uitm.edu.my/
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
description This paper presents Centre-based hard clustering approaches for clustering Y-STR data. Two classical partitioning techniques: Centroid-based partitioning technique and Representative object-based partitioning technique are evaluated. The k-Means and the k-Modes algorithms are the fundamental algorithms for the centroid-based partitioning technique, whereas the k-Medoids is a representative object-based partitioning technique. The three algorithms above are experimented and evaluated in partitioning Y-STR haplogroups and Y-STR Surname data. The overall results show that the centroid-based partitioning technique is better than the representative object-based partitioning technique in clustering Y-STR data.
format Article
author Seman, Ali
Abu Bakar, Zainab
Mohd. Sapawi, Azizian
spellingShingle Seman, Ali
Abu Bakar, Zainab
Mohd. Sapawi, Azizian
Centre-based hard clustering algorithms for Y-STR data / Ali Seman, Zainab Abu Bakar and Azizian Mohd. Sapawi
author_facet Seman, Ali
Abu Bakar, Zainab
Mohd. Sapawi, Azizian
author_sort Seman, Ali
title Centre-based hard clustering algorithms for Y-STR data / Ali Seman, Zainab Abu Bakar and Azizian Mohd. Sapawi
title_short Centre-based hard clustering algorithms for Y-STR data / Ali Seman, Zainab Abu Bakar and Azizian Mohd. Sapawi
title_full Centre-based hard clustering algorithms for Y-STR data / Ali Seman, Zainab Abu Bakar and Azizian Mohd. Sapawi
title_fullStr Centre-based hard clustering algorithms for Y-STR data / Ali Seman, Zainab Abu Bakar and Azizian Mohd. Sapawi
title_full_unstemmed Centre-based hard clustering algorithms for Y-STR data / Ali Seman, Zainab Abu Bakar and Azizian Mohd. Sapawi
title_sort centre-based hard clustering algorithms for y-str data / ali seman, zainab abu bakar and azizian mohd. sapawi
publisher Faculty of Computer and Mathematical Sciences
publishDate 2010
url https://ir.uitm.edu.my/id/eprint/11101/1/11101.pdf
https://ir.uitm.edu.my/id/eprint/11101/
https://mjoc.uitm.edu.my/
_version_ 1736837184702382080
score 13.211869

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