Journal of Engineering and Applied Sciences
ISSN: Online 1818-7803ISSN: Print 1816-949x
Abstract
In this study, a new approach to combine multiple decision systems using multiple classifiers and rough sets methods is presented. This approach depends on our proposed algorithms that work to combine multiple decision systems by aggregating the lower and upper approximations. This improves the quality of decision rules by increasing the number of certain rules which enable us to make certain decisions. Our experiment results indicate that combining lower and upper approximations improves the quality of decision rules. Furthermore, it increases the classification accuracy computed by single and multiple classifiers compared to existing methods.
How to cite this article:
F. Algarni and E.I. Elsedimy. An Intelligent Classifier for Group Decision Making Based on Rough Sets.
DOI: https://doi.org/10.36478/jeasci.2020.1805.1808
URL: https://www.makhillpublications.co/view-article/1816-949x/jeasci.2020.1805.1808