Elsevier

Handbook of Statistics

Volume 2, 1982, Pages 267-284
Handbook of Statistics

12 Single-link clustering algorithms

https://doi.org/10.1016/S0169-7161(82)02015-XGet rights and content

Publisher Summary

This chapter focuses on the computational algorithms for the single-link clustering method that is one of the oldest methods of cluster analysis. This clustering method is also known by many other names because of the fact that it has been reinvented in different application areas and that there exist many very different computational algorithms corresponding to the single-link clustering model. Often this identity has gone unnoticed, as the new clustering methods are not always compared with the existing ones. Different clustering methods imply different definitions of what constitutes a “cluster” and should, thus, be expected to give different results for many data sets. A variety of algorithms to serve as a convenient source of algorithms for the single-link method are presented in the chapter. While the algorithms differ considerably in terms of their computational efficiency, even the least efficient algorithm may sometimes be useful for small data sets.

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