Glance at a(n) cv.glmnet object

Glance accepts a model object and returns a tibble::tibble() with exactly one row of model summaries. The summaries are typically goodness of fit measures, p-values for hypothesis tests on residuals, or model convergence information.

Glance never returns information from the original call to the modelling function. This includes the name of the modelling function or any arguments passed to the modelling function.

Glance does not calculate summary measures. Rather, it farms out these computations to appropriate methods and gathers the results together. Sometimes a goodness of fit measure will be undefined. In these cases the measure will be reported as NA.

# S3 method for cv.glmnet
glance(x, ...)

Arguments

x

A cv.glmnet object returned from glmnet::cv.glmnet().

...

Additional arguments. Not used. Needed to match generic signature only. Cautionary note: Misspelled arguments will be absorbed in ..., where they will be ignored. If the misspelled argument has a default value, the default value will be used. For example, if you pass conf.lvel = 0.9, all computation will proceed using conf.level = 0.95. Additionally, if you pass newdata = my_tibble to an augment() method that does not accept a newdata argument, it will use the default value for the data argument.

Value

A tibble::tibble with one-row with columns:

lambda.min

The value of the penalization parameter lambda that achieved minimum loss as estimated by cross validation.

lambda.1se

The value of the penalization parameter lambda that results in the sparsest model while remaining within one standard error of the minimum loss.

See also

glance(), glmnet::cv.glmnet()

Other glmnet tidiers: glance.glmnet, tidy.cv.glmnet, tidy.glmnet