Applying Variable Precision Rough Set for Clustering Diabetics Dataset

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. (Published)

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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.

Item Type: Article
Uncontrolled Keywords: Clustering; Rough set; Variable precision rough set model; Diabetic dataset
Subjects: Q Science > QA Mathematics
Faculty/Division: Faculty of Computer System And Software Engineering
Depositing User: Noorul Farina Arifin
Date Deposited: 06 Jun 2013 04:14
Last Modified: 15 Aug 2017 03:58
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