How to extract the CV errors for optimal lambda using glmnet package?

cross-validation, glmnet, mse, r

Solution

From `?cv.glmnet`:

# ...
# Value:
#
#     an object of class ‘"cv.glmnet"’ is returned, which is a list with
#     the ingredients of the cross-validation fit. 
#
# lambda: the values of ‘lambda’ used in the fits.
#
#   cvm: The mean cross-validated error - a vector of length
#       ‘length(lambda)’.
# ...

So in your case, the cross-validated mean squared errors are in `cv.fit$cvm` and the corresponding lambda values are in `cv.fit$lambda`.

To find the minimum MSE you can use `which` as follows:

i <- which(cv.fit$lambda == cv.fit$lambda.min)
mse.min <- cv.fit$cvm[i]

or shorter

mse.min <- cv.fit$cvm[cv.fit$lambda == cv.fit$lambda.min]

Problem

I'm using the glment package for regression in R. I do the cross validation using `cv.fit<-cv.glmnet(x,y,...)`, and I get optimum lambda using `cvfit$lambda.min`. but I want to also get the corresponduing `MSE`(mean square error) for that lambda. would someone help me to get it ?

Original source