Provides a simple (but efficient) implementation of the k-means clustering algorithm. The goal of this algorithm is to, given a list of n-dimensional points, regroup them in k groups, such that each point gets to be in the group to which it is the closest to (using the center of the group).

Sample output (after some gnuplot hackery -- see the tests dir in the repository): http://i.imgur.com/IpIPC.png

Expect some improvements on the initial clustering, thus resulting in a better clustering, for future versions.