I have data in which the number of negative cases in response is approximately 98% of the total sample size (total # records are approximately 1 million, Response is
binary). The positive cases are roughly 2%. What are the limitations of applying 'glm' and 'cart' on such data? What option do I have in such cases?
On test data I did get a very good AUC ~0.92. How much faith should I have in this model considering such a disparity in the number of cases in the positive and negative categories?