Relational fuzzy clustering has been developed for extracting intrinsic cluster structures of relational data and was extended to\r\na linear fuzzy clustering model based on Fuzzy c-Medoids (FCMdd) concept, in which Fuzzy c-Means-(FCM-) like iterative\r\nalgorithm was performed by defining linear cluster prototypes using two representative medoids for each line prototype. In this\r\npaper, the FCMdd-type linear clustering model is further modified in order to handle incomplete data including missing values,\r\nand the applicability of several imputation methods is compared. In several numerical experiments, it is demonstrated that some\r\npre-imputation strategies contribute to properly selecting representative medoids of each cluster.
Loading....