Feature Subset Selection Using a Fuzzy Method

This paper presents further experiments for the FUZZY-WRAPPER, a feature subset selection method based on the Wang & Mendel method to generate fuzzy rule bases. This method aims at providing a means of selecting features taking into consideration aspects of fuzzy logic based representations, such as number, shape, and distribution of fuzzy sets, and reasoning method. The main idea is to consider different parameters from the general ones considered in the classic filter approaches, which are widely used for the task of feature subset selection. Experiments and results with 8 datasets, using a novel method to define the number of fuzzy sets for attributes, are presented and discussed.