Finding Optimal K with the Silhouette Method in K-Means Clustering

Explains the silhouette method for determining the optimal number of clusters (K) in K-Means clustering, including calculation, interpretation, and differences from the elbow method. Evaluation combining three metrics—average, minimum, and negative scores—is key.