Clustering is one of the core tools used by the data miner. Clustering
allows us to group entities in a generally unguided fashion, according
to how similar they are. This is done on the basis of a measure of the
distance between entities. The aim of clustering is to identify
groups of entities that are close together but as a group are quite
separate from other groups.
package includes k-means with a choice of
distances like Eulidean and Spearman.
. We optimize implementation
(with a parallelized hierarchical clustering) and
allow the possibility of using different distances like
Eulidean or Spearman (rank-based metric).
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