I am trying to do "variable selection" using Elastic Net method (Matlab Lasso function with alpha of 0.5). I have 75 predictors in total (some are correlated with each other, hence using Elastic Net instead of Lasso), and I would like to get a subset of them, which are good predictors for my outcome.
So my question is: How can I calculate something like R-Square that show how much of my outcome is explained by these selected variables?
1) If I use the selected variables in a multiple linear regression model, is the R-Square gonna be valid, since my variables are correlated?
2) Can I calculate cross-validated R-Square (using leave-one-out) to get a more accurate R-Square?
3) Is there any other way than calculating R-Square that I show my variable selection method predicts well?