You could do a hierarchical clustering, then look at the height of the last combination relative to the other heights, for your data:
> tmp <- hclust( dist( c(1,2,3,2,3,1,2,3,400,300,400) ) ) > tmp2 <- hclust( dist( c(400,402,405, 401,410,415, 407,412) ) ) > tmp$height [1] 0 0 0 0 0 0 1 2 100 399 > tmp2$height [1] 1 2 2 2 5 7 15 You still need to make some assumptions and come up with a method for choosing a cutoff, but this may help get you started. -- Gregory (Greg) L. Snow Ph.D. Statistical Data Center Intermountain Healthcare greg.s...@imail.org 801.408.8111 > -----Original Message----- > From: r-help-boun...@r-project.org [mailto:r-help-boun...@r- > project.org] On Behalf Of Ralf B > Sent: Wednesday, May 05, 2010 3:18 PM > To: r-help@r-project.org > Subject: [R] Dynamic clustering? > > Are there R packages that allow for dynamic clustering, i.e. where the > number of clusters are not predefined? I have a list of numbers that > falls in either 2 or just 1 cluster. Here an example of one that > should be clustered into two clusters: > > two <- c(1,2,3,2,3,1,2,3,400,300,400) > > and here one that only contains one cluster and would therefore not > need to be clustered at all. > > one <- c(400,402,405, 401,410,415, 407,412) > > Given a sufficiently large amount of data, a statistical test or an > effect size should be able to determined if a data set makes sense to > be divided i.e. if there are two groups that differ well enough. I am > not familiar with the underlying techniques in kmeans, but I know that > it blindly divides both data sets based on the predefined number of > clusters. Are there any more sophisticated methods that allow me to > determine the number of clusters in a data set based on statistical > tests or effect sizes ? > > Is it possible that this is not a clustering problem but a > classification problem? > > Ralf > > ______________________________________________ > 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. ______________________________________________ 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.
