I'm trying to determine number of clusters for k-means using
sklearn.metrics.silhouette_score. I have computed it for
range(2,50) clusters. How to interpret this? What number of clusters should I choose?
Silhouette measures BOTH the separation between clusters AND cohesion in respective clusters.
Intuitively speaking, it is the difference between separation B (average distance between each point and all points of its nearest cluster) and cohesion A (average distance between each point and all other points in its cluster) divided by max(A,B).
It is a value between -1 and 1, the higher the better (negative value means that the point is more closer to the nearest cluster than to its own, which is quite a problem).