On Tue, 2 Oct 2012 14:32:12 -0400 John Sorkin <jsor...@grecc.umaryland.edu> wrote:
> Ranjan, > Thank you for your help. What eludes me is how one computes the distance from > each cluster for each subject. For my first subject, datascaled[1,], I have > tried to use the following: > v1 <- sum(fit$centers[1,]*datascaled[1,]) > v2 <- sum(fit$centers[2,]*datascaled[1,]) > v3 <- sum(fit$centers[2,]*datascaled[1,]) > hoping the max(v1,v2,v3) would reproduce the group assignment, i.e. simply > assign the subject to the group that gives the largest value, but it does > not. How is the distance to the three clusters computed for each subject? > Thanks, > John Well, it should be: v <- vector(length = 3) for (i in 1:3) v[i] <- sum((fit$centers[i, ] - datascaled[1, ])^2) whichmin(v) should provide the cluster assignment. Btw, there is a better, more efficient and automated way to do this, i.e. avoid the loop using matrices and arrays and apply, but I have not bothered with that here. Ranjan -- Important Notice: This mailbox is ignored: e-mails are set to be deleted on receipt. For those needing to send personal or professional e-mail, please use appropriate addresses. ____________________________________________________________ GET FREE SMILEYS FOR YOUR IM & EMAIL - Learn more at http://www.inbox.com/smileys Works with AIM?, MSN? Messenger, Yahoo!? Messenger, ICQ?, Google Talk? and most webmails ______________________________________________ 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.
