Models associated with regression and classification data approaches all have these important parts except: 

a. Identifying which variables (we’ll call these independent variables) might help predict an outcome (we’ll call this the dependent variable). 

b. The functional form of the relationship (linear, nonlinear, etc.). 

c. The numeric parameters of the model (detailing the relative weights of each of the variables associated with the prediction). 

d. Test data.