SilhouettesΒΆ
Silhouettes is a method for validating clusters of data. Particularly, it provides a quantitative way to measure how well each item lies within its cluster as opposed to others. The Silhouette value of a data point is defined as:
Here, is the average distance from the i
th point to other points within the same cluster. Let be the average distance from the i
th point to the points in the k
th cluster. Then is the minimum of all over all clusters that the i
th point is not assigned to.
Note that the value of is not greater than one, and that is close to one indicates that the i
th point lies well within its own cluster.

silhouettes
(assignments, counts, dists) Compute silhouette values for individual points w.r.t. a given clustering.
Parameters:  assignments – the vector of assignments
 counts – the number of points falling in each cluster
 dists – the pairwise distance matrix
Returns: It returns a vector of silhouette values for individual points. In practice, one may use the average of these silhouette values to assess given clustering results.

silhouettes
(R, dists) This method accepts a clustering result
R
(of a subtype ofClusteringResult
).It is equivalent to
silhouettes(assignments(R), counts(R), dists)
.