Mean square point-centroid distance: not yet calculated

The $k$-means algorithm is an iterative method for clustering a set of $N$ points (vectors) into $k$ groups or clusters of points.

### Algorithm

Repeat until convergence:

Find closest centroid

Find the closest centroid to each point, and group points that share the same closest centroid.

Update centroid

Update each centroid to be the mean of the points in its group.

Find closest centroid