clustEval {iterClust} | R Documentation |
A sample cluster-wise clustering robustness evaluation framework (described in "Examples" section, used as default in iterClust framework). Customized frameworks can be defined following rules specified in "Usage", "Arguments" and "Value" sections.
clustEval(dset, iteration, clust)
dset |
(numeric matrix) features in rows and observations in columns |
iteration |
(positive integer) specifies current iteration |
clust |
return value of coreClust |
a numeric vector, specifies the clustering robustness (higher value means more robust) of each clustering scheme
DING, HONGXU (hd2326@columbia.edu)
clustEval <- function(dset, iteration, clust){ dist <- as.dist(1 - cor(dset)) clustEval <- vector("numeric", length(clust)) for (i in 1:length(clust)){ clustEval[i] <- mean(silhouette(clust[[i]], dist)[, "sil_width"])} return(clustEval)}