Introduction - If you have any usage issues, please Google them yourself
The ultimate goal of this program is to form a set of standards for clustering, scalable tools. Including the contents of 1 clustering algorithm: Kmeans and Kmedoid algorithm, FCMclust, GKclust, GGclust algorithm 2. Assessment classified prototypes: the program can draw two-dimensional image on the results of clustering 3 Verify: Program to provide an algorithm to each authentication mechanism, the statistics of each clustering algorithm Partition Coefficient (PC), Classification Entropy (CE), Partition Index (SC), Separation Index (S), Xie and Beni' s Index (XB), Dunn' s Index (DI) and Alternative Dunn Index (DII) of several metrics.