In this section, we discuss the hierarchical clustering technique and its computational challenges. An example of using the bisecting K-means algorithm of hierarchical clustering with Spark MLlib will be shown too for a better understanding of hierarchical clustering.
Hierarchical clustering (HC)
An overview of HC algorithm and challenges
A hierarchical clustering technique is computationally different from the centroid-based clustering in the way the distances are computed. This is one of the most popular and widely used clustering analysis technique that looks to build a hierarchy of clusters. Since a cluster usually consists of multiple objects, there will be other candidates to compute the distance too. Therefore, with...
