https://www.mathworks.com/help/stats/clustering.evaluation.silhouetteevaluation-class.html
Silhouette Value
The silhouette value for each point is a measure of how similar that point is to points in its own cluster, when compared to points in other clusters. The silhouette value for the i
th point, Si
, is defined as
Si = (bi-ai)/ max(ai,bi)
where ai
is the average distance from the i
th point to the other points in the same cluster as i
, and bi
is the minimum average distance from the i
th point to points in a different cluster, minimized over clusters.
The silhouette value ranges from -1 to +1. A high silhouette value indicates that i
is well-matched to its own cluster, and poorly-matched to neighboring clusters. If most points have a high silhouette value, then the clustering solution is appropriate. If many points have a low or negative silhouette value, then the clustering solution may have either too many or too few clusters. The silhouette clustering evaluation criterion can be used with any distance metric.
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