What Is the Difference Between Hierarchical and Partitional clustering?

Clustering is an unsupervised learning technique which is exploratory in nature and does not have a defined target or output. Clustering is often done to undercover hidden patterns within a dataset or for real-world uses such as market segmentation.

In this post, I would be mainly discuss about the difference between Hierarchical and Partitional clustering.

What Is Hierarchical Clustering?

Hierarchical agglomerative clustering is one of the main types of clustering algorithm and works using the following steps:

1. Each item within a dataset starts as an individual cluster (AKA: singletons)
2. The algorithm computes the proximity amongst each cluster
3. It then proceeds to merge each pair of closest clusters and computes the new proximity amongst remaining clusters
4. This process is then repeated until there is one cluster left

A typical representation of Hierarchical Clustering is represented using a Dendrogram

Example of a Dendrogram

What Is Partitional…