Sorry, to solve your question I had tried: data(faithful) kmeans(faithful[c(1:20),1],10) Error: empty cluster: try a better set of initial centers
But when I run this a second time it will be ok. It seems, that kmeans has problems to initialize good starting points, because of the random choose of these starting initial points. With kmeans(data,k,centers=c(...) the problem can be solved. Generally, the starting points can be choose equidistant on a hyperplane of the data, which is also a simple way to get the intitial points (www.fuzzyclustering.de , fc-package of Höppner, manual). Thank you for your comment, Matthias -----Ursprüngliche Nachricht----- Von: Unung Istopo Hartanto [mailto:[EMAIL PROTECTED] Gesendet: Dienstag, 11. Mai 2004 16:23 An: TEMPL Matthias Betreff: Re: [R] Probleme with Kmeans... Hello Matthias, I think kmeans able to process only one variable. It's an example, but give me a clearly explanation if i make a mistake. > univ [1] 0.7051308 0.9126754 0.6170866 0.6663761 5.8541014 0.6665355 0.9695508 [8] 1.1980253 0.9489970 0.9058717 4.0864110 0.9962518 0.7530303 1.0312622 [15] 5.0822132 3.1867548 2.3203937 0.5405755 3.6957646 0.8957396 0.8477315 [22] 0.6210427 0.8471373 3.5451798 0.4220632 0.5377178 0.3173005 0.7181018 [29] 0.9034660 1.2406042 0.9529861 3.3889001 0.8462411 0.8338748 1.8540691 [36] 1.3624104 6.9509700 > kmeans(univ,ncl) $cluster [1] 5 3 5 5 4 5 3 3 3 3 1 3 5 3 4 1 2 5 1 3 3 5 3 1 5 5 5 5 3 3 3 1 3 3 2 3 4 $centers [,1] 1 3.5806021 2 2.0872314 3 0.9808016 4 5.9624282 5 0.5968146 $withinss [1] 0.4622251 0.1087293 0.3637454 1.7637280 0.1768656 $size [1] 5 2 16 3 11 Thanks a lot, Unung Istopo On Tue, 2004-05-11 at 17:19, TEMPL Matthias wrote: > Hello, > When clustering with kmeans, your data should have more than one > variable. Matthias ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html