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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 !

Welcome to Stack Exchange! You don't need to say thank you but if you get a useful answer remember to up vote and accept it if it answers your question. – Robert de Graaf – 2016-06-28T10:43:59.110

Can you clarify what do you mean by

mathematically incorrect? That would help the community provide a better answer. – wabbit – 2016-06-28T14:50:50.530