Applying variable precision rough set for clustering diabetics dataset

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 roughset 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. © 2014 SERSC.