cross validation after lasso

I used cross validation to select lambda. Then I performed lasso and get non zero coefficients (features). Shall I perform cross validation for these non zero coefficients as a kind of validation?

• I am not clear about your question. What do you mean by "features selected by LASSO as a kind of validation for selected features". Also, I am not clear about "using different thresholds"? and also " input matrix for LASSO". I suggest you to ask your question in a more formal way. – TPArrow Apr 11 '16 at 12:28
• I agree, your question is not clear at all. Perhaps you could provide a small working example? – StatGrrl Apr 11 '16 at 13:51
• No, CV is enough. Unless you want to go back and do a different CV (ie 10-fold, etc). This would be a better way to "validate" your results if you feel uneasy. – jchaykow Apr 12 '16 at 3:50

That is, if you do a cross validation for this final model validation step, you need to need to wrap another "outer" cross validation around all calculations that lead to the LASSO-model (including the "inner" cross validation you used for tuning of $\lambda$).