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Applying Variable Precision Rough Set for Clustering Diabetics Dataset
- Source :
- International Journal of Multimedia and Ubiquitous Engineering. 9:219-230
- Publication Year :
- 2014
- Publisher :
- Global Vision Press, 2014.
-
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.
- Subjects :
- Computational model
Fuzzy clustering
General Computer Science
business.industry
Computer science
Correlation clustering
Process (computing)
Pattern recognition
Medical decision making
computer.software_genre
Rough set
Artificial intelligence
Data mining
business
Cluster analysis
computer
Variable precision
Subjects
Details
- ISSN :
- 19750080
- Volume :
- 9
- Database :
- OpenAIRE
- Journal :
- International Journal of Multimedia and Ubiquitous Engineering
- Accession number :
- edsair.doi...........694cc6a66c8e64fce51225b9c047fdcc