I'd like to announce the availability of a new library for hybrid hierarchical clustering, "hybridHclust". The library has been uploaded to CRAN and is now available.
The library implements a hybrid of top-down and bottom-up hierarchical clustering. Along the way, the idea of a "mutual cluster" is developed. A mutual cluster is a set of observations whose largest within-group distance is smaller than the distance to the closest point outside the set. The hybrid method is a top-down approach that preserves such mutual clusters. Mutual clusters are useful in their own right, and have the interesting property that they cannot be "broken" by many bottom-up methods. Tools that graphically integrate mutual clusters into bottom-up methods are also included in the library. Lastly, an implementation of Michael Eisen's bottom-up clustering algorithm is also in the library. A paper, soon to appear in Biostatistics, describes this work: Chipman, H., and Tibshirani, R. "Hybrid Hierarchical Clustering with Applications to Microarray Data", available at http://ace.acadiau.ca/math/chipmanh/papers/chipman-tibshirani-2003-modif ied.pdf There's an online tutorial at http://ace.acadiau.ca/math/chipmanh/hybridHclust/index.html Hugh Chipman and Robert Tibshirani -- Hugh Chipman -- Associate Professor and Canada Research Chair in Mathematical Modelling -- Department of Mathematics and Statistics, Acadia University -- Wolfville, Nova Scotia, Canada B4P 2R6 -- (902) 585-1525, Fax: (902) 585-1074 -- http://ace.acadiau.ca/math/chipmanh/homepage.htm _______________________________________________ R-packages mailing list [EMAIL PROTECTED] https://stat.ethz.ch/mailman/listinfo/r-packages ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
