Hi, I am a new R user. I have seen the use of kmeans in clustering. However, I would like to ask how I can add more constraints to the kmeans. For example, I have a set of data for a 10 nodes network,
price = c(84, 96, 57, 53, 90, 94, 81, 66, 93, 54) I want to use K mean to to group this set of data into two group. However, nodes in the same group should be in the same group. they are connected as below. mymatrix <- rbind( + c(1,1,2,3,3,3,2,1,1,1), + c(1,1,1,2,2,2,1,1,1,1), + c(2,1,1,1,1,1,1,1,2,2), + c(3,2,1,1,1,1,1,2,3,3), + c(3,2,1,1,1,1,1,2,3,3), + c(3,2,1,1,1,1,1,2,2,2), + c(2,1,1,1,1,1,1,1,2,2), + c(1,1,1,2,2,2,1,1,1,1), + c(1,1,2,3,3,2,2,1,1,1), + c(1,1,2,3,3,2,2,1,1,1)) How can I do it in R. I greatly appreciate your help. I wish a happy Easter. Hanna [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.