SOA PAPredictive Analytics

For predicting claim severity that is strictly positive and right-skewed, the most appropriate GLM specification is:

Compared with ridge regression, lasso regression:

You suspect the effect of driver age on claim frequency differs by vehicle class (sports car vs sedan). Describe how you would test and, if warranted, incorporate this in a GLM, and how you would guard against overfitting.

Explain how k-fold cross-validation is used to select the lasso penalty parameter $\lambda$, and why choosing $\lambda$ to minimize training error would be inappropriate.