Combine clustering results using latent class analysis.
LCA(E, is.relabelled = TRUE, seed = 1)
a matrix of clusterings with number of rows equal to the number of cases to be clustered, number of columns equal to the clustering obtained by different resampling of the data, and the third dimension are the different algorithms. Matrix may already be two-dimensional.
FALSE the data will be relabelled using
the first clustering as the reference.
random seed for reproducibility
a vector of cluster assignments based on LCA