Authors : Vijaya , Aayushi Sinha and Ritika Bateja
Abstract: Clustering is the process of grouping the datasets into various clusters such that the variations within the clusters are very small but between the clusters are remarkable. Clustering has a wide application field like data concept construction, simplification, pattern recognition, etc. Clustering methods are mainly classified into two groups, hierarchical and partitioning. The hierarchical clustering method defines the hierarchy of clusters by splitting and merging them whereas partitioning method involves defining partitions and their evaluation based on some criteria. Thus, clustering algorithms chosen need to be efficient. This study focuses on different types of hierarchical clustering algorithms as well as various advanced clustering algorithms based on hierarchical clustering. It also discusses their strengths and weaknesses in detail.
Vijaya , Aayushi Sinha and Ritika Bateja, 2017. A Review on Hierarchical Clustering Algorithms. Journal of Engineering and Applied Sciences, 12: 7501-7507.