Applying Variable Precision Rough Set for Clustering Diabetics Dataset

Applying Variable Precision Rough Set for Clustering Diabetics Dataset

Computational models of the artificial intelligence such as rough set theory have several applications. Rough set-based data clustering can be considered further as a technique for medical decision making. This paper presents the results of an experimental study of a rough-set based clustering techn...

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Main Authors: Herawan, Tutut, Wan Maseri, Wan Mohd, Noraziah, Ahmad
Format: Article
Language:English
Published: SERSC 2014
Subjects:
QA Mathematics
Online Access:http://umpir.ump.edu.my/id/eprint/3788/
http://umpir.ump.edu.my/id/eprint/3788/
http://umpir.ump.edu.my/id/eprint/3788/1/2013_maseri_Applying.pdf
id ump-3788
recordtype eprints
spelling ump-37882017-08-15T03:58:00Z http://umpir.ump.edu.my/id/eprint/3788/ Applying Variable Precision Rough Set for Clustering Diabetics Dataset Herawan, Tutut Wan Maseri, Wan Mohd Noraziah, Ahmad QA Mathematics Computational models of the artificial intelligence such as rough set theory have several applications. Rough set-based data clustering can be considered further as a technique for medical decision making. This paper presents the results of an experimental study of a rough-set based clustering technique using Variable Precision Rough Set (VPRS). Here, we employ our proposed clustering technique [12] through a medical dataset of patients suspected diabetic. Our results indicate that the VPRS-based technique is better than that the standard rough set-based techniques in the process of selecting a clustering attribute. SERSC 2014 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/3788/1/2013_maseri_Applying.pdf Herawan, Tutut and Wan Maseri, Wan Mohd and Noraziah, Ahmad (2014) Applying Variable Precision Rough Set for Clustering Diabetics Dataset. International Journal of Multimedia and Ubiquitous Engineering (IJMUE), 9 (1). pp. 219-230. ISSN 1975-0080 http://www.sersc.org/journals/IJMUE/vol9_no1_2014/21.pdf
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
topic QA Mathematics
spellingShingle QA Mathematics
Herawan, Tutut
Wan Maseri, Wan Mohd
Noraziah, Ahmad
Applying Variable Precision Rough Set for Clustering Diabetics Dataset
description Computational models of the artificial intelligence such as rough set theory have several applications. Rough set-based data clustering can be considered further as a technique for medical decision making. This paper presents the results of an experimental study of a rough-set based clustering technique using Variable Precision Rough Set (VPRS). Here, we employ our proposed clustering technique [12] through a medical dataset of patients suspected diabetic. Our results indicate that the VPRS-based technique is better than that the standard rough set-based techniques in the process of selecting a clustering attribute.
format Article
author Herawan, Tutut
Wan Maseri, Wan Mohd
Noraziah, Ahmad
author_facet Herawan, Tutut
Wan Maseri, Wan Mohd
Noraziah, Ahmad
author_sort Herawan, Tutut
title Applying Variable Precision Rough Set for Clustering Diabetics Dataset
title_short Applying Variable Precision Rough Set for Clustering Diabetics Dataset
title_full Applying Variable Precision Rough Set for Clustering Diabetics Dataset
title_fullStr Applying Variable Precision Rough Set for Clustering Diabetics Dataset
title_full_unstemmed Applying Variable Precision Rough Set for Clustering Diabetics Dataset
title_sort applying variable precision rough set for clustering diabetics dataset
publisher SERSC
publishDate 2014
url http://umpir.ump.edu.my/id/eprint/3788/
http://umpir.ump.edu.my/id/eprint/3788/
http://umpir.ump.edu.my/id/eprint/3788/1/2013_maseri_Applying.pdf
first_indexed 2023-09-18T21:58:18Z
last_indexed 2023-09-18T21:58:18Z
_version_ 1777414227394297856

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