I am using sklearn random forest to predict the probability of win/lose in a card game. There are 4 features in my data set. Can I set the depth of one feature to be 1 while the depth of other features to be higher?
Such that the output will be in the form: for every combination of the first 3 features, there will be a threshold $T$ of the 4th feature.
For every $X1,X2,X3$ the following is true:
- if $X4<T$ then $y=0 $
- if $X4 >= T$ then $y=1$
The reason is that this feature is the hand strength of the player and y (the winning probability) is monotonically increasing in the hand strength. Thus I wish to get to a cutoff decision: for every combination of the first three features (X1,X2,X3) there is a Threshold $T$ such that, for hand strength greater than $T$, play Right, and for hand strength lower than $T$, play Left.
I am doing my first steps in Machine learning, so i will appreciate a simple solution.