merge, on the flight, two adjacent clusters in order to allow better clustering scheme, if needed, and to avoid new computation of the unsupervised mode.
mergeClusters(object, whichOnes)
Arguments
object: an object of class unsupervised.
whichOnes: which clusters are needed to be merged ? Should be two adjacent ones.
## not run## Crabs data # data(crabs, package = "MASS")## and more about# ?crabs## model : commit 4 clusters# crabs.rufUnsupervised = unsupervised.randomUniformForest(crabs, # categoricalvariablesidx = "all", nodesize = 5, threads = 1, clusters = 4)## visualize clusters and merge adjacent clusters# plot(crabs.rufUnsupervised)## we can first merge clusters 1 and 4## note that clusters may change if run again# crabs.rufUnsupervisedNew = mergeClusters(crabs.rufUnsupervised, c(1,4))## one can assess the fitting, comparing old and new model# crabs.rufUnsupervised# crabs.rufUnsupervisedNew## visualize new model# plot(crabs.rufUnsupervisedNew)## merge new clusters 1 and 2 and look if it will be better# crabs.rufUnsupervisedNewest = mergeClusters(crabs.rufUnsupervisedNew, c(1,2))# crabs.rufUnsupervisedNewest# plot(crabs.rufUnsupervisedNewest)## NOTE : mergeClusters() provides choice on how to choose and assess clusters## using simply visualization.