Simultaneous Application of Fuzzy Clustering and Correspondence Analysis

Abstract

An algorithm which simultaneously applies the Fuzzy c-Means clustering and the correspondence analysis is developed. Maximization of an objective function yields memberships of fuzzy clusters and assigns values to categories and patterns. A regularization term is introduced in the objective function and we apply the Lagrangean multiplier method and an adaptive method using eigenvalues in the correspondence analysis.