stepFlexclust {flexclust}R Documentation

Run Flexclust Algorithms Repeatedly

Description

Runs clustering algorithms repeatedly for different numbers of clusters and returns the minimum within cluster distance solution for each.

Usage

stepFlexclust(x, k, nrep=3, verbose=TRUE, FUN = kcca, drop=TRUE,
              group=NULL, simple=FALSE, save.data=FALSE, ...)

## S4 method for signature 'stepFlexclust, missing':
plot(x, y,
  type=c("barplot", "lines"), totaldist=NULL,
  xlab=NULL, ylab=NULL, ...)

## S4 method for signature 'stepFlexclust':
getModel(object, which=1)

Arguments

x, ... passed to kcca or cclust.
k A vector of integers passed in turn to the k argument of kcca
nrep For each value of k run kcca nrep times and keep only the best solution.
FUN Cluster function to use, typically kcca or cclust.
verbose If TRUE, show progress information during computations.
drop If TRUE and K is of length 1, then a single cluster object is returned instead of a "stepFlexclust" object.
group An optional grouping vector for the data, see kcca for details.
simple Return an object of class kccasimple?
save.data Save a copy of x in the return object?
y Not used.
type Create a barplot or lines plot.
totaldist Include value for 1-cluster solution in plot? Default is TRUE if K contains 2, else FALSE.
xlab, ylab Graphical parameters.
object Object of class "stepFlexclust".
which Number of model to get. If character, interpreted as number of clusters.

Author(s)

Friedrich Leisch

Examples

data("Nclus")
plot(Nclus)

cl1 = stepFlexclust(Nclus, k=2:7, FUN=cclust)
cl1

plot(cl1)

getModel(cl1, 4)

opar=par("mfrow")
par(mfrow=c(2,2))
for(k in 3:6){
  image(getModel(cl1, as.character(k)), data=Nclus)
  title(main=paste(k, "clusters"))
}
par(opar)

[Package flexclust version 1.1-2 Index]