## Regression with ExtraTrees:
n <- 1000 ## number of samples
p <- 5 ## number of dimensions
x <- matrix(runif(n*p), n, p)
y <- (x[,1]>0.5) + 0.8*(x[,2]>0.6) + 0.5*(x[,3]>0.4) + 0.1*runif(nrow(x))
et <- extraTrees(x, y, nodesize=3, mtry=p, numRandomCuts=2, ntree=500)
## random selection of trees:
trees <- sample(c(FALSE, TRUE), replace=TRUE, et$ntree)
et2 <- selectTrees(et, selection=trees)
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