Hierarchical Clustering Two main types of hierarchical clustering ◆ Agglomerative a Start with the points as individual clusters a At each step, merge the closest pair of clusters until only one cluster (or k clusters)left ◆ Divisive: a Start with one, all-inclusive cluster o At each step, split a cluster until each cluster contains a point (or there are k clusters a Traditional hierarchical algorithms use a similarity or distance matrix Merge or split one cluster at a timeHierarchical Clustering ◼ Two main types of hierarchical clustering ◆ Agglomerative:  Start with the points as individual clusters  At each step, merge the closest pair of clusters until only one cluster (or k clusters) left ◆ Divisive:  Start with one, all-inclusive cluster  At each step, split a cluster until each cluster contains a point (or there are k clusters) ◼ Traditional hierarchical algorithms use a similarity or distance matrix ◆ Merge or split one cluster at a time 14