Search code examples
rcross-validationglmnetmse

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

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 ?

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]