I'm trying to explain a count variable and a continious variable > 0 with GLM, using R. In order to improve the quality of the regression, I want to add some interactions that can be useful for the model. As I'm a newbie in machine learning, I want to know if RF and GBM can help me to determine useful interactions. I saw that interact.gbm can assess the relative strength of interaction effects in non-linear models. The question is : Will it be "mathematically" correct to add variables with important strength of interaction in order to reduce MSE/Deviance ?
Thank you !