Desktop Survival Guide
by Graham Williams
The aim of clustering is to identify groups of data points that are close together but as a group are separate from other groups.
The amap 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).