How to specify split in a decision tree in R programming?

Question

I am trying to apply decision tree here. Decision tree takes care of splitting at each node itself. But at first node I want to split my tree on the basis of \"Age\". How do

Answer 1

At every iteration, a decision tree will choose the best variable for splitting (either based on information gain / gini index, for CART, or based on chi-square test as for conditional inference tree). If you have better predictor variable that separates the classes more than that can be done by the predictor Age, then that variable will be chosen first.

I think based on your requirement, you can do the following couple of things:

(1) Unsupervised: Discretize the Age variable (create bins e.g., 0-20, 20-40, 40-60 etc., as per your domain knowledge) and subset the data for each of the age bins, then train a separate decision tree on each of these segments.

(2) Supervised: Keep on dropping the other predictor variables until Age is chosen first. Now, you will get a decision tree where Age is chosen as the first variable. Use the rules for Age (e.g., Age > 36 & Age <= 36) created by the decision tree to subset the data into 2 parts. On each of the parts learn a full decision tree with all the variables separately.

(3) Supervised Ensemble: you can use Randomforest classifier to see how important your Age variable is.