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mkmeans | See Also

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.

See Also

kmeans, fkmeans, gkclus

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