SilhouettenIndex
The Silhouette Index is a statistical measure used to evaluate the quality of clusters in a dataset. It quantifies how similar an object is to its own cluster compared to other clusters. The index ranges from -1 to 1, where a higher value indicates better-defined clusters. A value of 0 suggests overlapping clusters, and a negative value indicates that objects might have been assigned to the wrong cluster.
The Silhouette Index is calculated for each data point and then averaged to produce an overall measure
s(i) = (b(i) - a(i)) / max(a(i), b(i))
where a(i) is the average distance from the data point i to all other points in the
The Silhouette Index is widely used in various fields such as machine learning, data mining, and image
However, the Silhouette Index has some limitations. It assumes that clusters are convex and isotropic, which