how does k means work?
The k-means clustering algorithm attempts to split a given anonymous data set (a set containing no information as to class identity) into a fixed number (k) of clusters. Initially k number of so called centroids are chosen. ... Each centroid is thereafter set to the arithmetic mean of the cluster it defines.