The clusters are relabelled to obtain a unique labeling.
relabel(object, by, ...)
# S4 method for kccasimple,character
relabel(object, by, which = NULL, ...)
# S4 method for kccasimple,integer
relabel(object, by, ...)
# S4 method for kccasimple,missing
relabel(object, by, ...)
# S4 method for stepFlexclust,integer
relabel(object, by = "series", ...)
# S4 method for stepFlexclust,missing
relabel(object, by, ...)An object of class "kccasimple" or
"stepFlexclust".
If a character vector, it needs to be one of "mean",
"median", "variable", "manual",
"centers", "shadow", "symmshadow" or
"series".
If missing, "mean" or "series" is used depending on if
object is of class "kccasimple" or
"stepFlexclust".
If an integer vector, it needs to indicate the new ordering.
Either an integer vector indiating the ordering or a vector of length one indicating the variable used for ordering.
Currently not used.
If by is a character vector with value "mean" or
"median", the clusters are ordered by the mean or median values
over all variables for each cluster. If by = "manual"
which needs to be a vector indicating the ordering. If
by = "variable" which needs to be indicate the variable
which is used to determine the ordering. If by is
"centers", "shadow" or "symmshadow", cluster
similarities are calculated using clusterSim and used to
determine an ordering using seriate from package
seriation.
If by = "series" the relabeling is performed over a series of
clustering to minimize the misclassification.