A Semi-Fuzzy Partition Algorithm

Aim of the present paper is to introduce a semi-fuzzy partition algorithm in order to take into account both the advantages of fuzzy and hard classification methods. It keeps the information of mixed objects without losing the sharpness of the pure objects. The assignment rule of the objects to the classes, in fuzzy or in hard way, is based on the empirical distributions of the squared Mahalanobis distances of the objects from the baricenters (or prototypes) of each fuzzy class.