Genetic fuzzy classifier with fuzzy rough sets for imprecise data
Janusz T. Starczewski, Robert K. Nowicki, Bartosz A. Nowak · 2014
The main problem addressed in this paper is to handle adequately imprecision of input data by means of a combination of fuzzy methods with the rough set theory. We will make use of fuzzy rough sets derived as rough approximations of fuzzy antecedent sets by non-singleton fuzzy premise sets in a fuzzy classifier. Adaptation of the parameters of this system will be done by the standard genetic algorithm.