Simultaneous application of clustering and correspondence analysis

An algorithm which simultaneously applies the fuzzy c-means clustering algorithm and the correspondence analysis is developed. Maximization of an objective function yields membership of fuzzy clusters and assigns values to categories and individuals in the correspondence analysis. A regularization term is introduced into the objective function. The algorithms are Picard iteration through necessary conditions of the optimality for the objective function. An adaptive method using eigenvalues is introduced