I used cv.glmnet to create a model using one dataset ("Dataset 1"), but now I would like to look at performance (e.g., AUC) when predicting outcomes for new data ("Dataset 2"). I know that I can use predict.glmnet to predict new data, but the output is just a list of predicted outcomes for each observation in Dataset 2. How do I actually summarize the predictive performance (e.g., AUC) of a cv.glmnet model on on Dataset 2?
For example, it would be nice to be able to save the predictions for Dataset 2 as a new column. From there I can just calculate performance myself manually, but ideally I'd like to know if there is a way to have these indices calculated for me.