TY  - JOUR
T1  - A Review on Hierarchical Clustering Algorithms
AU - , Vijaya AU - Sinha, Aayushi AU - Bateja, Ritika 
JO  - Journal of Engineering and Applied Sciences
VL  - 12
IS  - 24
SP  - 7501
EP  - 7507
PY  - 2017
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2017.7501.7507
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2017.7501.7507
KW  - Clustering
KW  -data mining
KW  -hierarchical clustering algorithms
KW  -partitioning
KW  -construction
KW  -splitting
AB  - 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.
ER  -