Hi, I have a question on decision trees used in the context of a retention/churn model.
If I run a decision tree (after training it on a sample data set) then what do I get as output?
In other words how can I identify where the new unclassified data have been placed in the trees branches, in order to do some actions on them (e.g customer care actions, etc.) ?. Can I also get a score applied to each new data that has been classified according to the likelihood of churn?
Not sure if I was clear, if you need more details please ask!
Thanks in advance, Giovanni