Dear WizaRds,
although this might be a trivial question to the community, I was
unable to
find anything solving my problem in the help files on CRAN. Please help.
Suppose I have 4 variables and want to use all possible combinations:
1,2
1,3
1,4
2,3
2,4
3,4
for a further kmeans partitioning.
I tried permutations() of package e1071, but this is not what I need. Thank you
for your help and support.
mark.
---------------------------------------------------------------------
Additionally: For anybody who is willing to offer some advise, here is my
complete approach:
library(e1071)
mat <- matrix( c(6,7,8,2,3,4,12,14,14, 14,15,13,3,1,2,3,4,2,
15,3,10,5,11,7,13,6,1, 15,4,10,6,12,8,12,7,1), ncol=9, byrow=T )
rownames(mat) <- paste("v", 1:4, sep="" )
tmat <- t(mat)
cluster <- c(1, 2, 1, 3, 3, 3, 1, 2, 2)
centroids <- matrix( 0, ncol=3, nrow=4 )
obj <- vector(mode="list", length=3)
for (j in 1:4){
for (i in 1:3){
where <- which(cluster==i) # which obj is in which class?
centroids[j,i] <- mean( tmat[ where,j ] )
obj[[i]] <- tmat[where,]
}
}
colnames(centroids) <- paste( c("Cluster"), 1:3)
rownames(centroids) <- rownames(mat)
centroids
obj
## now I want to do kmeans of all possible variable pairs, e.g. v1 and v3
## automization in a second step later
wjk <- kmeans(tmat[,c(1,3)], centers=centroids[c(1,3),], iter.max=10,
algorithm="MacQueen") ## obviously wrong
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