In kmeans() in stats one gets an error message with the default
clustering algorithm if centers = 1. Its often useful to calculate
the sum of squares for 1 cluster, 2 clusters, etc. and this error
complicates things since one has to treat 1 cluster as a special case.
A second reason is that easily getting the 1 cluster sum of squares
makes it easy to calculate the between cluster sum of squares when
there is more than 1 cluster.
I suggest adding the line marked ### to the source code of kmeans (the
other lines shown are just ther to illustrate context). Adding this
line forces kmeans to use the code for algorithm 3 if centers is 1.
This is useful since unlike the code for the default algorithm, the
code for algorithm 3 succeeds for centers = 1.
if(length(centers) == 1) {
if (centers == 1) nmeth <- 3 ###
k <- centers
Also note that KMeans in Rcmdr produces a betweenss and a tot.withinss
and it would be nice if kmeans in stats did that too:
> library(Rcmdr)
> str(KMeans(USArrests, 3))
List of 6
$ cluster : Named int [1:50] 1 1 1 2 1 2 3 1 1 2 ...
..- attr(*, "names")= chr [1:50] "Alabama" "Alaska" "Arizona" "Arkansas" ...
$ centers : num [1:3, 1:4] 11.81 8.21 4.27 272.56 173.29 ...
..- attr(*, "dimnames")=List of 2
.. ..$ : chr [1:3] "1" "2" "3"
.. ..$ : chr [1:4] "Murder" "Assault" "UrbanPop" "Rape"
$ withinss : num [1:3] 19564 9137 19264
$ size : int [1:3] 16 14 20
$ tot.withinss: num 47964 <=================
$ betweenss : num 307844 <=================
- attr(*, "class")= chr "kmeans"
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