library(tree)
tr1<-tree(a1~.,data=algae[,1:12])
#get cv value
tr1.cv<-cv.tree(tr1)

#do this 10 times total since 10 partitions are random
#it doesn't need to be 10 times. just do enough times.

for (i in 2:10){
	tr1.cv$dev<-tr1.cv$dev+cv.tree(tr1)$dev
}

tr1.cv$dev<-tr1.cv$dev/10

plot(tr1.cv)

##find the best size
##get the size with min deviance

final.tr<-prune.tree(tr1,best=4)

final.tr

plot(final.tr)
text(final.tr)