K-Means clustering: how it works and how to evaluate it

K-Means iteratively assigns points and recomputes cluster centroids as cluster means until convergence, minimizing within-cluster variance. The elbow method and silhouette coefficient are commonly used to determine the optimal number of clusters.

2026-08-30 ~ 2026-08-30 · 4 related posts

• K-Means Update Step: Recalculating Centroids — mdancho84 · 2026-08-30
• K-Means Iteration: Repeating Until Centroids Converge — mdancho84 · 2026-08-30
• Silhouette Score: Measuring Cluster Cohesion — mdancho84 · 2026-08-30
• Elbow Method: Evaluating Optimal Cluster Count — mdancho84 · 2026-08-30