Tuning of a Fuzzy Classifier Derived from Data by Solving Inequalities

摘要

In this paper, we develop a novel method for tuning parameters known as the sensitivity parameters of mem- bership functions used in a fuzzy classifier. The proposed method performs tuning by solving a set of inequalities. Each inequality represents a range of the ratio of the sensitivity parameters be tween the corresponding pair of classes. The range ensures the maximum classification rate for data of the two corresponding classes used for tuning. First, we discuss how such a set of in- equalities is derived. We then propose an algorithm to solve the derived set of inequalities.