I have a large distance matrix $3400\times 3400$.
I need to cluster them hierarchically and then cut the tree into clusters (like a partitional approach).
Which algorithm is most sensitive to finding natural clusters in the data based on the distance matrix?
How can I evaluate the result? I am planning on using average silhouette coefficient of the tree at various levels to identify the 'natural' clusters from the tree.