I am very new to machine learning modeling, but I encountered a feature selection problem that I hope can get your insights on:
- For example, I have A,B,C,D as my independent variables and y as my dependent variable. The end user is more interested in C & D's impact on y since A and B are factors that the user don't have much power to change.
- But in the modeling, we see that A and B have very large feature importance in predicting y, while C and D have low prediction power.
- In this case, should I train the model only based on C&D or I should train the model based on ABCD？
- or is there any feature engineering I should do?