Clustering in an Object-Oriented Environment
Mia Hubert and
Peter Rousseeuw ()
Journal of Statistical Software, 1997, vol. 001, issue i04
This paper describes the incorporation of seven stand-alone clustering programs into S-PLUS, where they can now be used in a much more flexible way. The original Fortran programs carried out new cluster analysis algorithms introduced in the book of Kaufman and Rousseeuw (1990). These clustering methods were designed to be robust and to accept dissimilarity data as well as objects-by-variables data. Moreover, they each provide a graphical display and a quality index reflecting the strength of the clustering. The powerful graphics of S-PLUS made it possible to improve these graphical representations considerably. The integration of the clustering algorithms was performed according to the object-oriented principle supported by S-PLUS. The new functions have a uniform interface, and are compatible with existing S-PLUS functions. We will describe the basic idea and the use of each clustering method, together with its graphical features. Each function is briefly illustrated with an example.
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https://www.jstatsoft.org/index.php/jss/article/do ... i04/clus_help.tar.gz
https://www.jstatsoft.org/index.php/jss/article/do ... 04/clus_splus.tar.gz
https://www.jstatsoft.org/index.php/jss/article/do ... clus_examples.tar.gz
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