Fuzzy c-Varieties Clustering for Vertically Distributed Datasets
Katsuhiro Honda, Kohei Kunisawa, Seiki Ubukata, Akira Notsu · Procedia Computer Science · 2021
Fuzzy c-varieties (FCV) is a linear fuzzy clustering method, whose clustering criterion is constructed by replacing the fuzzy c-means (FCM) prototypes with linear varieties, and has been utilized for local principal component analysis. In this paper, the FCV iterative algorithm is modified for handling vertically distributed datasets under consideration of privacy preservation. A cryptographic calculation scheme is realized by utilizing the least square criterion without eigen solutions. The characteristics of the proposed algorithm is demonstrated through numerical experiments.