Hierarchy Clustering Implementation on YouTube's Top Data

Abstract

Clustering is a method or process of grouping datasets into various clusters to produce variations in smaller clusters. Clustering has broad application fields such as data concept construction, pattern recognition, web search, simplification, security, and several other areas. Clustering methods are classified into two types, hierarchies and partitions. The hierarchical clustering method defines the cluster hierarchy by separating and combining them, whereas the partitioning method involves defining and evaluating sections based on criteria. Thus, the selected clustering algorithm must be efficient. This article focuses on clustering algorithms for obtaining and processing YouTube Channel Top Data.