I am currently trying to fit a conditional inference tree using the
ctree function in the
party package. So far I see that some of the arguments that control the depth of the tree include
minbucket. My goal is to try and create a fully grown tree so that each terminal node has 100% classification (I understand that this means that the tree would be rather large). However even when changing these parameters, e.g.
minsplit = 0, minbucket = 0, mincriterion = 0, I still do not get a full grown tree. Some of the terminal nodes give me a probability of being in one class or another.
I am curious as to why this tree is not grown all the way? Are there any arguments that I am not writing in, or is it not possible for these trees to be pure at the temrinal nodes?