Talk:Hierarchical clustering: Difference between revisions

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There is a 1967 paper, published in Psychometrika, titled "Hierarchical Clustering Schemes", by S. C. Johnson (yes, that's me...). It was extensively cited in the 70's and 80's, in part because Bell Labs gave away a FORTRAN program for free that did a couple of the methods described in the paper. The paper pointed out that there is a correspondence between hierarical clusterings and a kind of data metric called an ultrametric -- whenever you have a hierarchical clustering, it implies an ultrametic, and conversely. [[Special:Contributions/76.244.36.165|76.244.36.165]] ([[User talk:76.244.36.165|talk]]) 19:14, 18 October 2012 (UTC) Stephen C Johnson

US Patent application 14/718,804 achieves sub-quadratic complexity for dissimilarity measures based on distances in a Euclidean vector space.

http://arxiv.org/abs/1109.2378 is a good survey of the algorithms.

== Example for Agglomerative Clustering edit ==