Random Vector Clustering Using Fuzzy C-Means

The fuzzy c-means (FCM) clustering algorithm has long been used to cluster numerical data. Recently FCM has also been used to cluster data sets consisting of mixtures of numerical, interval, and fuzzy data. Here the range of applicability of FCM is shown to include data sets whose feature values are continuous random variables. Parametric and nonparametric approaches are given and demonstrated using a simple computational example