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...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
SERSC
2014
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| Subjects: | |
| 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 |
| Summary: | 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. |
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