What are the types of hierarchical clustering?

There are two types of hierarchical clustering. They are agglomerative clustering and divisive clustering.

Agglomerative clustering: In this algorithm, initially every data object will be treated as a cluster. In each step, the nearest clusters will fuse together and form a bigger cluster. Ultimately, all the clusters will merge together. Finally, a single cluster, which encompasses all the data points, will remain.

Divisive clustering: This is the opposite of the agglomerative clustering. In this type, all the data objects will be considered as single clusters. In each step, the algorithm will split the cluster. This will repeat until only single data points remain, which will be considered as singleton clusters.