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performs multi prototypes clustering
Syntax
[cg,cp] = mkmeans(d,n,p)
[cg,cp] = mkmeans(d,n,p,l)
Description
[cg,cp] = mkmeans(d,n,p)
Finds the center of the clusters cg and there associated
prototypes cp using a new clustering method developped in IRIDIA.
d is the data set, n the number of clusters and p
the number of prototypes by cluster.
cg is a n rows matrix (one for each cluster).
cp is a p rows and n columns 3D matrix.
[cg,cp] = mkmeans(d,n,p,l)
l is the weight of the center of the cluster in
the definition of the cost function minimised by the clustering method.
kmeans, fkmeans, gkclus