Hallo! I applied kmeans to my data:
kcluster= kmeans((mydata, 4, iter.max=10) table(code, kcluster$cluster) If I run this code again, I get a different result as with the first trial (I understand that this is correct, since kmeans starts randomly with assigning the clusters and therefore the outcomes can be different) But is there a way to stabilize the cluster (meaning finding the one cluster that appears the most often in 10 trials)? Thank you for any ideas, Julia -- ______________________________________________ R-help@r-project.org mailing list 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.
