There are no big differences between growing trees with tree or rpart. Both work in similar ways and both depend on the dtree package, more or less. As the time-cost of growing trees is often too small, I can't see a reason not to try both, hence explaining how to grow trees using both.
The following shows how to recursively grow a decision-tree model using the tree package:
if(!require(tree)){install.packages('tree')}library(tree)tree_tree <- tree(vote ~ . , data = dt_Chile[-i_out,], method = 'class', mindev = 0)
The very first couple of lines are performing a check-install on the tree package and then loading and attaching the whole package. After these two lines, an object called tree_tree is being created. ...
