LASSO workflow for cross validation and final model
Dec 13, 2018 7:55 AM(193 views)
Please check my understanding of how CV is working in JMP for LASSO (or any other regularization method). Suppose I choose 5-fold CV. Here is what I think happens...
We loop through all the lambdas. For each lambda we generate 5 errors and average these. At the end we use the minimum error to identify the optimal lambda_star. Now we use all the data, along with lambda_star to find the final model (the set of coefficients).
My understanding is that the in-sample error is what we calculate with the final model on all the data. What about the out-of-sample error? I've seen leave-one-out used to estimate this. Does JMP calculate this and show it in the report, and if so, how is that done? Also can lambda_star be displayed. I saw a related discussion for retrieving the tuning parameter but I'm hoping to avoid JSL if I can.