Agglomerative Hierarchical Clustering Algorithm- A Review
K. Sasirekha, P. Swathi Baby
Abstract
K. Sasirekha, P. Swathi Baby
Abstract
Clustering is a task of assigning a set of objects into groups called clusters. In data mining, hierarchical clustering is a method of cluster analysis which seeks to build a hierarchy of clusters. Strategies for hierarchical clustering generally fall into two types:Agglomerative: This is a bottom approach: each observation starts in its own cluster, and pairs of clusters are merged as one moves up the hierarchy.Divisive: This is a top approach: all observations start in one cluster, and splits are performed recursively as one moves down the hierarchy.
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Clustering is a task of assigning a set of objects into groups called clusters. In data mining, hierarchical clustering is a method of cluster analysis which seeks to build a hierarchy of clusters. Strategies for hierarchical clustering generally fall into two types:Agglomerative: This is a bottom approach: each observation starts in its own cluster, and pairs of clusters are merged as one moves up the hierarchy.Divisive: This is a top approach: all observations start in one cluster, and splits are performed recursively as one moves down the hierarchy.
Key concepts: Hierarchical clustering, Single-linkage clustering, Hierarchy, Complete-linkage clustering, Cluster analysis, Hierarchical clustering of networks, Cluster (spacecraft), Computer science