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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Abstract
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 |
| URI: | http://umpir.ump.edu.my/id/eprint/3788 |
| Download Statistic: | View Download Statistics |
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