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

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