Methods of Hierarchical Clustering

Abstract

We survey agglomerative hierarchical clustering algorithms and discuss efficient implementations that are available in R and other software environments. We look at hierarchical self-organizing maps, and mixture models. We review grid-based clustering, focusing on hierarchical density-based approaches. Finally we describe a recently developed very efficient (linear time) hierarchical clustering algorithm, which can also be viewed as a hierarchical grid-based algorithm.

21 pages, 2 figures, 1 table, 69 references

References in corpus (1)

• Symmetry in Data Mining and Analysis: A Unifying View based on Hierarchy

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