Search! the rseek.org site gives many hits for "self organizing maps", including the som package among others.
-- Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Tue, Oct 9, 2018 at 11:14 PM A DNA RNA <email2m...@gmail.com> wrote: > Dear All, > > Who can I use Self Organizing Map (SOM) results to cluster samples? I have > tried following but this gives me only the clustering of grids, while I > want to cluster (150) samples: > > library(kohonen) > iris.sc <- scale(iris[, 1:4]) > iris.som <- som(iris.sc, grid=somgrid(xdim = 3, ydim=3, topo="hexagonal"), > rlen=100, alpha=c(0.05,0.01)) > ##hierarchical clustering > groups <- 3 > iris.hc <- cutree(hclust(dist(iris.som$codes[[1]])), groups) > iris.hc > #V1 V2 V3 V4 V5 V6 V7 V8 V9 > #1 1 2 1 1 2 3 3 2 > > > Can anyone help me with this please? > -- > Tina > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
