Abstract
This paper addresses the relationship between the Visual Assessment of cluster Tendency (VAT) algorithm and single linkage hierarchical clustering. We present an analytical comparison of the two algorithms in conjunction with numerical examples to show that VAT reordering of dissimilarity data is directly related to the clusters produced by single linkage hierarchical clustering. This analysis is important to understanding the underlying theory of VAT and, more generally, other algorithms that are based on VAT-ordered dissimilarity data.
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