Partitional or Hierarchical Clustering?

Previously most work related to clustering in the image domain has been partitional (or fuzzy partitional). I've not yet thought through the merits of hierarchical clustering as applied to the image domain or to the clustering of structured data.

Partitional clustering simply slices the data space into clusters. However, hierarchical clustering provides more information. It tells you what clusters there would be depending on the level of granularity asked for. You can have one big cluster that covers all the data instances, and as you increase the granularity you see the sub-clusters separating off. This information is usually and naturally presented in the form of a dendogram.

See wikipedia for more information on these distinctions: http://en.wikipedia.org/wiki/Data_clustering