glmnet objects are created from the glmnet package, leveraged to fit generalized linear models via penalized maximum likelihood.
Usage
# S3 method for class 'glmnet'
axe_call(x, verbose = FALSE, ...)
Examples
library(parsnip)
# Wrap a parsnip glmnet model
wrapped_parsnip_glmnet <- function() {
some_junk_in_environment <- runif(1e6)
model <- logistic_reg(penalty = 10, mixture = 0.1) %>%
set_engine("glmnet") %>%
fit(as.factor(vs) ~ ., data = mtcars)
return(model$fit)
}
out <- butcher(wrapped_parsnip_glmnet(), verbose = TRUE)
#> ✔ Memory released: 1.08 kB
#> ✖ Disabled: `print()` and `summary()`