obsEval: Observation-wise Clustering Robustness Evaluation
In hd2326/iterClust: Iterative Clustering

Description Usage Arguments Value Author(s) Examples

A sample observation-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.

1	obsEval(dset, clust, iteration)

`dset`	(numeric matrix) features in rows and observations in columns
`clust`	optimal return value of coreClust
`iteration`	(positive integer) specifies current iteration

a numeric vector, specifies the clustering robustness (higher value means more robust) of each observation under the optimal clustering scheme

DING, HONGXU (hd2326@columbia.edu)

obsEval <- function(dset, clust, iteration){
    dist <- as.dist(1 - cor(dset))
    obsEval <- vector("numeric", length(clust))
    return(silhouette(clust, dist)[, "sil_width"])}