Togaware DATA MINING
Desktop Survival Guide
by Graham Williams
Google


K-Means:
Clustering



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).



Subsections

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