The following are all benefits of generalized additive models (GAMs), EXCEPT: O GAMs are less computationally demanding than linear regression. O GAMs can model non-linear relationships that standard linear regression will miss. O GAMs can potentially make more accurate predictions of the response than linear regression can. O One can examine the effect of each predictor on the response individually while holding all of the other predictors fixed