Correlation based generating rules for fuzzy classification

Abstract

Automated acquisition of rules is a very important issue in knowledge engineering. In this paper, a new method for generating fuzzy rules from numerical data for fuzzy classification problems based on the correlation analysis between two fuzzy sets has been proposed. Experimental results and comparison with Yuan and Shaw's method are presented as well.