I am trying to build a regression tree with 70 attributes where the business team wants to fix the first two levels namely country and product type.To achieve this,I have two proposals:
1.Build a separate tree for each combination of country & product type and use subsets of the data accordingly and pass on to respective tree for prediction.Saw here in comments.I have 88 levels in country and 3 levels in product type so it will generate 264 trees.
2.Build a basic tree with two variables namely country and product type with appropriate cp value to generate all combination as leaf nodes(264).Build a second tree with rest all variables and stack tree one upon tree two as a single decision tree.
I don't think the first one is the right way to do.Also, struck on how to stack the trees in second approach, even if it is not the right way would love to know how to achieve this.
Please guide me to approach the problem.Thanks.