Consider the following dataset, with (only) ten points x=c(.4,.55,.65,.9,.1,.35,.5,.15,.2,.85) y=c(.85,.95,.8,.87,.5,.55,.5,.2,.1,.3) plot(x,y,pch=19,cex=2) We want to get – say – two clusters. Or more specifically, two sets of observations, each of them sharing some similarities. Since the number of observations is rather small, it is actually possible to get an exhaustive list of all partitions, and to minimize some criteria, such...