partition.tree(tree, label="yval", add=F, ordvars, ...)
If the tree contains one predictor, the predicted value (a regression tree) or the probability of the first class (a classification tree) is plotted against the predictor over its range in the training set.
If the tree contains two predictors, a plot is made of the space covered by those two predictors and the partition made by the tree is superimposed.
tree
data(iris) ir.tr <- tree(Species ~., iris) ir.tr ir.tr1 <- snip.tree(ir.tr, nodes = c(12, 7)) summary(ir.tr1) par(pty="s") plot(iris[, 3],iris[, 4], type="n", xlab="petal length", ylab="petal width") text(iris[, 3], iris[, 4], c("s", "c", "v")[iris[, 5]]) par(cex=1.5) partition.tree(ir.tr1, add=T, cex=1.5) par(cex=1)