I am not aware of an implementation of the algorithm you describe. If you are not locked to that particular approach, function diana() in package cluster performs polythetic, hierarchical partitioning which could be used to get your starting cluster centers.
Scanning over a paper by Su and Dy (you didn't give us a full citation, this one was published in Intelligent Data Analysis 2007 (11): 319-338), they conclude: "In case one cannot afford several random start runs, our deterministic initialization methods provide reasonable alternatives." Unless your data is enormous, you can surely afford multiple random starts. Just use the nstart= argument in the kmeans() function. It will run that many kmeans analyses and pick the one that produces the minimum within sum of squares. ------------------------------------- David L Carlson Associate Professor of Anthropology Texas A&M University College Station, TX 77840-4352 -----Original Message----- From: [email protected] [mailto:[email protected]] On Behalf Of Safiye Celik Sent: Thursday, September 12, 2013 7:37 PM To: [email protected] Subject: [R] Deterministic initialization for k-means Hi, I want to cluster my data points into K clusters using k-means algorithm, and I want to use a deterministic (non-random) initialization scheme which is also a "good" start. I found a paper by Ting Su and Jennifer Dy named "A Deterministic Method for Initializing K-means Clustering" and I wonder if there is a way in R to partition the points in the way that is described in this paper. "Starting from an initial cluster that contains the entire data set, the method iteratively selects the cluster with the greatest SSE and divides it into two subclusters using a hyperplane that passes through the cluster centroid and is orthogonal to the principal eigenvector of the cluster covariance matrix. This procedure is repeated until K clusters are obtained." If I get the final K centers from this partitioning, then I can give those centers to R's kmeans algorithm to let it converge. Is there a built-in R function to get such an initial partitioning? Thanks! -- -safiye [[alternative HTML version deleted]] ______________________________________________ [email protected] 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. ______________________________________________ [email protected] 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.
