Clustering / Classification

Hi,

I have a huge NxN ( thousands of elements ) correlation matrix, I need
to cluster this data ( of N elements ) to X groups of the most similar
items, this can be done using K-Means & friends though it would take
allot of time, I wonder, taking in mind I already have the correlation
matrix ( hence the similarity of each element to the other ) is there
a way, more efficient then K-means ( and friends ) to cluster the data
to X groups ?

Any help would be appreciated.

Thanks,
Nadav Rubinstein.

.

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