Fuzzy Feature Subset Selection Using the Wang & Mendel Method

Abstract

The dimension of a knowledge domain can impact the use of genetic algorithms to automatically design fuzzy rule bases, since the search space for the genetic algorithm increases exponentially with thenumber of features. Filters are a possible approach to reduce the number of features. However, the filter approach does not take into consideration the particular aspects of fuzzy logic when selecting or ranking features. This work presents a method for feature subset selection using the Wang & Mendel method as the base for a wrapper. Experimental results are presented and discussed.