Visualizing K-Means equilibria

Very neat to see the how the centroids move to the equilibria. Also interesting to look at other point distributions to see what happens in more pathological cases. (For the interested, I once made a kmeans visualization http://www.naftaliharris.com/blog/visualizing-k-means-cluste..., there is one in the sibling comment to this, and many others can be found with a little googling).

Really nice. I had built something similar in Python and matplotlib [ https://github.com/sidthekidder/kmeans-visualize/blob/master... ]. Of course your implementation is 100x, and I gained a better understanding from reading the source.

Nice set of images showing the result of tweaking different parameters:

https://twitter.com/BlackiLi/status/689860531293941762

Bostock is really a master of his own language... and is very expressive with it. Even as many (including myself) are grappling with the basics.

This particular algorithm seems to be related to the Voronoi Tesselation -- deciding which points get allocated to each of the k different centers

http://bl.ocks.org/mbostock/4060366