>>>>> On Mon, 12 May 2008 19:24:55 +0200, >>>>> cgenolin (c) wrote:
> Hi the devel list, > I am using K means with a non standard distance. As far as I see, the > function kmeans is able to deal with 4 differents algorithm, but not > with a user define distance. > In addition, kmeans is not able to deal with missing value whereas > there is several solution that k-means can use to deal with them ; one > is using a distance that takes the missing value in account, like a > distance with Gower adjustement (which is the regular distance dist() > used in R). > So is it possible to adapt kmeans to let the user gives an argument > 'distance to use'? As Bill Venables already pointed out that makes not too much sense, especially as there are already R functions for doing that. Package flexclust implements a k-means-type clustering algorithm where the user can provide arbitrary distance measures, have a look at http://www.stat.uni-muenchen.de/~leisch/papers/Leisch-2006.pdf The code you need to write for using a new distance measure is minimal, and there are two examples in the paper describing in detail what needs to be done. Hope this helps, Fritz Leisch -- ----------------------------------------------------------------------- Prof. Dr. Friedrich Leisch Institut für Statistik Tel: (+49 89) 2180 3165 Ludwig-Maximilians-Universität Fax: (+49 89) 2180 5308 Ludwigstraße 33 D-80539 München http://www.statistik.lmu.de/~leisch ----------------------------------------------------------------------- Journal Computational Statistics --- http://www.springer.com/180 Münchner R Kurse --- http://www.statistik.lmu.de/R ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel