Clustering incomplete relational data using the non-Euclidean relational fuzzy c-means algorithm

摘要

An approach for clustering on the basis of incomplete dissimilarity data is given. The data is first completed using simple triangle inequality-based approximation schemes and then clustered using the non-Euclidean relational fuzzy c- means algorithm. Results of numerical tests are included.