Axing an elnet. — axe-elnet • butcher

elnet objects are created from the glmnet package, leveraged to fit generalized linear models via penalized maximum likelihood.

Usage

# S3 method for elnet
axe_call(x, verbose = FALSE, ...)

Arguments

x: A model object.
verbose: Print information each time an axe method is executed. Notes how much memory is released and what functions are disabled. Default is FALSE.
...: Any additional arguments related to axing.

Value

Axed model object.

Examples

# Load libraries
library(parsnip)
library(rsample)

# Load data
split <- initial_split(mtcars, prop = 9/10)
car_train <- training(split)

# Create model and fit
elnet_fit <- linear_reg(mixture = 0, penalty = 0.1) %>%
  set_engine("glmnet") %>%
  fit_xy(x = car_train[, 2:11], y = car_train[, 1, drop = FALSE])

out <- butcher(elnet_fit, verbose = TRUE)
#> ✔ Memory released: 312 B