glmnet - variable importance?

Question

I´m using the glmnet package to perform a LASSO regression. Is there a way to get the importance of the individual variables that were selected? I thought about ranking the coef

Answer 1

It's pretty easy to use the contents of the cv.glmnet object to create an ordered list of coefficients...

coefList <- coef(cv.glmnet.MOD, s='lambda.1se')
coefList <- data.frame(coefList@Dimnames[[1]][coefList@i+1],coefList@x)
names(coefList) <- c('var','val')

coefList %>%
  arrange(-abs(val)) %>%
  print(.,n=25)

NOTE: as other posters have commented...to get a like for like comparison you need to scale/z-score your numeric variables prior to modelling step...otherwise a large coefficient value can be assigned to a variable with a very small scale i.e. range(0,1) when placed in a model with variables with very large scales i.e. range(-10000,10000) this will mean that your comparison of coefficient values is not relative and therefore meaningless in most contexts.