I am trying to build a logistic regression model. I have some categorical variables for which I have created dummy variables (eg. Department). I also have some numeric variables like Age and Tenure.
My question is which of the approach should I use-
- Should I use a combination of dummy variables and numeric variables as an input to my logistic model.
- Or, should I create categories of numeric variables based on response rate and use these categories to create dummy variables for numeric variables as well.
In first approach I am afraid that I numeric variable will become highly significant and cause overfitting. Also, they will reduce the real "significance" of dummy variables. In second approach I am afraid that I will loose a lot of information.