  A new cluster validity index is proposed for fuzzy clusters obtained from
fuzzy c-means algorithm. The proposed validity index exploits inter-cluster
proximity between fuzzy clusters. Inter-cluster proximity is used to measure
the degree of overlap between clusters. A low proximity value refers to
well-partitioned clusters. The best fuzzy c-partition is obtained by minimizing
inter-cluster proximity with respect to c. Well-known data sets are tested to
show the effectiveness and reliability of the proposed index.
