# How to interpret silouette coefficient?

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?

They are all bad. A good Silhouette would be 0.7

• I'm clustering text data. So, I can compute the most popular word in each cluster. When I see at top_n words, I can conclude that algorishm works well. But I don't know what k is the best number of clusters. I don't understand why this metric shows so bad result. – Толкачёв Иван Oct 8 '16 at 22:49