Hierarchical clustering results in a series of clustering results:
- the results start off with each object in their own cluster and end with all of the objects in the same cluster
- the intermediate clusters are created by a series of merges
- the resultant tree-like structure is called a dendrogram
You build a binary tree of the data that successively merges similar groups of points, visualising this tree provides a useful summary of the data.
This resolves an issue with flat clustering (k-Means) where structure is lost.