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$centers[2,]*datascaled[1,]) hoping the max(v1,v2,v3) would reproduce the group assignment, i.e. simply assign the subject to the group that gives the largest value, but it does not. How is the distance to the three clusters computed for each subject? Thanks, John
John David Sorkin M.D., Ph.D. Chief, Biostatistics and Informatics University of Maryland School of Medicine Division of Gerontology Baltimore VA Medical Center 10 North Greene Street GRECC (BT/18/GR) Baltimore, MD 21201-1524 (Phone) 410-605-7119 (Fax) 410-605-7913 (Please call phone number above prior to faxing)>>> Ranjan Maitra <maitra.mbox.igno...@inbox.com> 10/2/2012 1:59 PM >>> John, On Tue, 2 Oct 2012 11:35:12 -0400 John Sorkin <jsor...@grecc.umaryland.edu> wrote: > Window XP > R 2.15 > > I am running a cluster analysis in which I ask for three clusters (see code > below). The analysis nicely tells me what cluster each of the subjects in my > input dataset belongs to. I would like two pieces of information > (1) for every subject in my input data set, what is the probability of the > subject belonging to each of the three cluster K-means provides hard clustering, whatever cluster has closest mean gets the assignment. > (2) given a new subject, someone who was not in my original dataset, how can > I determine their cluster assignment? Look at the distance between the subject the cluster means: the one that is closest gets assigned the cluster. If you are looking for probabilistic clustering (under Gaussian mixture model assumptions), you could use model-based clustering: one R package is mclust. Btw, note that kmeans is very sensitive to initialization (as is mclust): you may want to try several random starts (for kmeans), at the very least. Use the argument "nstart" with a huge number. HTH, Ranjan > Thanks, > John > > # K-Means Cluster Analysis > jclusters <- 3 > fit <- kmeans(datascaled, jclusters) # 3 cluster solution > > and fit$cluster tells me what cluster each observation in my input dataset > belongs to (output truncated for brevity): > > > fit$cluster 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 > > 17 . . . . > 1 1 1 1 3 1 1 1 1 2 1 2 1 1 1 1 1 . . . . > How do I get probability of being in cluster 1, cluster 2, and cluster 3 for > a given subject, e.g datascaled[1,]?How do I get the cluster assigment for a > new subject?Thanks,John > John David Sorkin M.D., Ph.D. > Chief, Biostatistics and Informatics > University of Maryland School of Medicine Division of Gerontology > Baltimore VA Medical Center > 10 North Greene Street > GRECC (BT/18/GR) > Baltimore, MD 21201-1524 > (Phone) 410-605-7119 > (Fax) 410-605-7913 (Please call phone number above prior to faxing) > Confidentiality Statement: > This email message, including any attachments, is for the sole use of the > intended recipient(s) and may contain confidential and privileged > information. Any unauthorized use, disclosure or distribution is prohibited. > If you are not the intended recipient, please contact the sender by reply > email and destroy all copies of the original message. -- 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. ____________________________________________________________ FREE ONLINE PHOTOSHARING - Share your photos online with your friends and family! Visit http://www.inbox.com/photosharing to find out more! Confidentiality Statement: This email message, including any attachments, is for the sole use of the intended recipient(s) and may contain confidential and privileged information. Any unauthorized use, disclosure or distribution is prohibited. If you are not the intended recipient, please contact the sender by reply email and destroy all copies of the original message.
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