silhouette analysis

Silhouette analysis is a method used to evaluate how well data points fit into their assigned groups or clusters. It measures the similarity of each point to others in its own group compared to points in other groups. A high silhouette score indicates that the point is well-matched with its own cluster and distinct from others, suggesting good clustering. Conversely, a low score suggests the point may be misplaced. Overall, silhouette analysis helps determine the optimal number of clusters and assess the quality of the grouping, making it a valuable tool for understanding the structure within data.