Cross Validated is a question and answer site for people interested in statistics, machine learning, data analysis, data mining, and data visualization. It only takes a minute to sign up.
Sign up to join this community
I have been trying to understand the results of a CRT decision tree, my question is if the terminal nodes should be mutually exclusive? I am asking this because by reading the terminal nodes some variables seems to overlap each other.
For instance some terminal nodes "share" the same profession:
Node 23: carpenter, plumber, sole trader, truck driver
Node 24: plumber, truck driver, teacher, retired.
Probably I am reading the results incorrectly because it should not happen, at least in theory.
The terminal nodes are mutually exclusive in that observations cannot be classified into more than one node.
They are not mutually exclusive in the sense that they can use the same characteristics/variables to classify observations.
The issue here may be that often in statistical packages like R the node number has little meaning (at least to me). So that terminal node 23 and 24 are not necessarily two branches from a single node - in fact they are likely to be branches of different nodes and they thus can use the same characteristics.
Hope that makes sense
