LCE: Linkage Clustering Ensemble

In diceR: Diverse Cluster Ensemble in R

Linkage Clustering Ensemble

Description

Generate a cluster assignment from a CTS, SRS, or ASRS similarity matrix.

Usage

LCE(E, k, dc = 0.8, R = 10, sim.mat = c("cts", "srs", "asrs"))

Arguments

E	is an array of clustering results. An error is thrown if there are missing values. impute_missing() can be used beforehand.
k	requested number of clusters
dc	decay constant for CTS, SRS, or ASRS matrix
R	number of repetitions for SRS matrix
sim.mat	similarity matrix; choices are "cts", "srs", "asrs".

Value

a vector containing the cluster assignment from either the CTS, SRS, or ASRS similarity matrices

Author(s)

Johnson Liu

See Also

Other consensus functions: CSPA(), LCA(), k_modes(), majority_voting()

Examples

data(hgsc)
dat <- hgsc[1:100, 1:50]
x <- consensus_cluster(dat, nk = 4, reps = 4, algorithms = c("km", "hc"),
progress = FALSE)
## Not run: 
LCE(E = x, k = 4, sim.mat = "asrs")

## End(Not run)

x <- apply(x, 2:4, impute_knn, data = dat, seed = 1)
x_imputed <- impute_missing(x, dat, nk = 4)
LCE(E = x_imputed, k = 4, sim.mat = "cts")

diceR documentation built on May 29, 2024, 8:54 a.m.