Models associated with regression and classification data approaches have all have these important parts except: Multiple Choice identifying which variables $($we$\text{'}$ll call these independent variables$)$ might help predict an outcome $($we$\text{'}$ll call this the dependent variable$).$ the functional form of the relationship $($linear$,$ nonlinear, etc.$).$ the numeric parameters of the model $($detailing the relative weights of each of the variables associated with the prediction$).$ test data.