I need a general guide on what are the appropriate approaches to automated feature selection in multiple regression with categorical variables.
In my case, I have several numeric and categorical independent variables. I want to predict a numeric value and I am going to make use of multiple regression, including these categorical variables according to the effect coding strategy (find effect coding ref. here).
My questions are:
I am familiar with stepwise feature selection methods that I used in logistic regression models. Are they likely to be successful in this case, too?
When is there a moment to apply such automated feature selection methods? I mean: if I run them after introducing effect-transformed variables, there is a possibility the method reject e.g. a part of effect-transformed variables, drawn from one categorical variable (this categorical variable is not fully represented then), isn't it? Is this a problem?
What are the most popular automated feature selection methods when dealing with categorical variables?