What is k-means clustering?

What is k-means clustering?

Approach: Describe iterative algorithm to partition data into k clusters.

Initialize k centroids. Repeat: assign each point to nearest centroid, recompute centroids as mean of points in cluster, until convergence. Minimizes within-cluster sum of squares.

Follow-up: How to choose k?

Key concepts: clustering, centroids, iterative algorithm.