obsEval {iterClust}R Documentation

Observation-wise Clustering Robustness Evaluation

Description

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.

Usage

obsEval(dset, clust, iteration)

Arguments

dset

(numeric matrix) features in rows and observations in columns

clust

optimal return value of coreClust

iteration

(positive integer) specifies current iteration

Value

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

Author(s)

DING, HONGXU (hd2326@columbia.edu)

Examples

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


[Package iterClust version 1.14.0 Index]