In GAM, a general approach is to use B-spline basis expansion to approximate the true nonparametric function. Usually the edge knots are chosen as the minimum and maximum of the training data (for continuous predictors). However, it is very possible that a predictor in the testing data fall outside of the range between the training minimum and maximum. The B-spline basis expansion on the training set was not defined on such values. What are the possible ways to handle these points?
(For example, how does the bs() function in R handle these points?)