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Silhouette score is bounded in the range of -1 to 1. The closest to 1, separation score is the largest, which indicates that an ideal silhouette coefficient is obtained, since separation score quantifies how dissimilar a sample is to other clusters and cohesion score tells how similar it is to the other samples in its own cluster. Silhouette definition, a two-dimensional representation of the outline of an object, as a cutout or configurational drawing, uniformly filled in with black, especially a black-paper, miniature cutout of the outlines of a person's face in profile. See more. In this blog , I am trying to explain tittle bit more on how to play more significant role in k-means clustering evaluation by silhouette analysis instead of elbow technique. Before go to this

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