Unsupervised

k-means is unsupervised learning’s hello world: pick \(k\) prototype points, assign every datum to its nearest prototype, move each prototype to the centre of its flock, repeat. 𐃏 it is fast, it always terminates, and it is wrong in ways that are so instructive that every clustering course starts here anyway.