I am working on financial prediction problem(time-series prediction problem).
I think feature engineering is importance in this problem. So i am careful to check the feature's effectiveness. And i perfer linear regression, because i think it's easy to explain, and I am not good at machine learning models
But i think i have another method: build a lot of features without careful check, select good model to handle it.
So, my question is:
In which model, add what kind of features, will harm this model's ability?
And Is there any models, i can just add without worrying the harm of trash features? in this model, what should i pay attention to?