Hey there! I got a pseudo code and don't know how to apply it to R, maybe someone can help me:
Input: A dataset X, kmax: maximum number of clusters, num_subsamples: number of subsamples. Output: S(i; k) - a distribution of similarities between partitions into k clusters of a reference clustering and clustering of subsamples; i = 1 to num_subsamples Requires: T = cluster(X): A hierarchical clustering algorithm L = cut-tree(T; k): produces a partition with k non-singleton clusters s(L1;L2): a similarity between two partitions 1: f = 0:8 2: T =cluster(X) fthe reference clustering 3: for i = 1 to num subsamples do 4: subi =subsamp(X; f) fsub-sample a fraction f of the datag 5: Ti=cluster(subi) 6: end for 7: for k = 2 to kmax do 8: L1=cut-tree(T; k) fpartition the reference clusteringg 9: for i = 1 to maximum iterations do 10: L2 =cut-tree(Ti; k) 11: S(i; k) = s(L2;L1) computed only on the patterns of subi. 12: end for 13: end for I am glad about any help, don't really know what to do! thanks, regards Julia -- ______________________________________________ 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.
