A student is trying to cluster some data. Tree-building things seem to be pretty hopeless (we've tried most of the ones in R, I think). Multi-dimensional scaling produces somewhat tantalising results: things do clump together somewhat, but the clusters overlap a lot. I was wondering if these was an artefact of squeezing it down to 2D, and whether 3D might be better. So loc <- cmdscale(dist(scale(log(data))), k=3) plot(loc) _but_ I still get a 2D plot.
I know about persp(), and a bunch of other things in R that give me a 3d view of a 2d field (plots of a function of 2 arguments, in other words). But I want to plot a bunch of 3D points and label them. If the worst comes to the worst, I'll dump them out in a file and use XLispStat to view them. I've asked previously whether there's a spinning plot in R, and have been told that there isn't and why. I've been given one anyway, but it calls Tcl/Tk, and for some reason that doesn't work in my setup. ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
