Random Forest pruning
The size of the trees can be a solution for you. Try to limit the size of the trees in the forest (max leaf noders, max depth, min samples split...).
I have sklearn random forest regressor. It's very heavy, 1.6 GBytes, and works very long time when predicting values.
I want to prune it to make lighter. As I know pruning is not implemented for decision trees and forests. I can't implement it by myself since tree code is written on C and I don't know it.
Does anyone know the solution?