For a set of clustering labels, this function computes the comembership of all pairs of observations. Basically, two observations are said to be comembers if they are clustered together.
a vector of
Tibshirani and Walther (2005) use the term 'co-membership', which we shorten to 'comembership'. Some authors instead use the terms 'connectivity' or 'co-occurrence'.
We use the
Rcpp package to improve the runtime
speed of this function.
a vector of
choose(n, 2) comembership bits
Tibshirani, R. and Walther, G. (2005), Cluster Validation by Prediction Strength, _Journal of Computational and Graphical Statistics_, 14, 3, 511-528. http://amstat.tandfonline.com/doi/abs/10.1198/106186005X59243.
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# We generate K = 3 labels for each of n = 10 observations and compute the # comembership for all 'n choose 2' pairs. set.seed(42) K <- 3 n <- 10 labels <- sample.int(K, n, replace = TRUE) comembership_out <- comembership(labels) comembership_out # Notice that the number of comemberships is 'n choose 2'. length(comembership_out) == choose(n, 2)
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