Perform the computations behind clustering procedures (e.g., K-means, hierarchical).

Free CAS MAS-II (Modern Actuarial Statistics II) lesson in Statistical Learning. 13 min read, ~1,904 words.

K-means minimizes total within-cluster sum of squares (WCSS),. You pick up front. K-means algorithm alternates: assign each point to its nearest centroid, then recompute centroids. WCSS strictly decreases each iteration and converges to a local (not global) optimum. Hierarchical clustering (agglomerative) starts with singletons and merges the two closest clusters...

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