library(cluster)
data(agriculture)
### pam() - Partitioning Around Medoids
part <- pam(agriculture, k=2)
plot(part, which.plots=1, labels=3, col.clus=3, lwd=2, main="PAM")
### diana() - Divisive Hierarchical Algorithm
hier <- diana(agriculture)
plot(hier, which.plots=2, lwd=2, main="DIANA")
### agnes() - Agglomerative Hierarchical Algorithm
### Visualizing clustering result
heatmap(as.matrix(t(agriculture)), Rowv=NA, labRow=c("GNP", "% in Agriculture"), cexRow=1,xlab="Country")
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