This is a deliberate limitation that allows for an optimization in the implementation. However, since the complexity of hierarchical clustering is cubic in the number of patterns, clustering so many patterns will take forever anyway.
1) What about removing this limitation to allow to do hierarchical clustering with more than 65,500 patterns even if I have to wait 3 days with a powerful machine?
2) Would you have any other suggestions on how to cluster this population based on a string distance without using a Hierarchical Clustering ?
But the problem is that with k-Medoids you cannot assign a cluster based on distance threshold as you can do with "Hierarchical Cluster Assigner". So the number of clusters is predetermined and so in my case it does not help very much.