Fuzzy c-Means Clustering for Mixed Databases

Abstract

Fuzzy c-Means (FCM) clustering is an unsupervised classification method for revealing intrinsic structure of multivariate data sets. It is, however, applicable to databases including only numerical variables. For analyzing the intrinsic feature of categorical data sets, the quantification of nominal variables estimates low dimensional scores. This paper proposes a new approach to the clustering of mixed databases including not only numerical variables but also categorical variables. The clustering technique uses an FCM-type simple iterative algorithm including a quantification step, in which the category scores are derived so that they are suited to the FCM clustering by considering cluster centers and memberships.