I have been recently come across a problem that entails using a decision tree that only uses one continuous variable to divide the predictor on multiple threshold, while some splits result in the same decision. The decision tree is as follows:
So I have two questions:
- Does it make sense to use one variable multiple times for dividing the predictor?
- Is it possible that two splits result in the same decision?
I didn't share any codes or data set because I just want to know whether this condition is possible and why we would prefer this.