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Machine Learning · k-means clustering
Unsupervised clustering with k-means: the assign/update loop, inertia, choosing k with the elbow and silhouette score.
- k-means alternates two steps: assign each point to the nearest centre, then move each centre to the mean of its points.
- The silhouette score compares how close a point is to its own cluster versus the next one.