model_fit objects are created from the parsnip package.
Usage
# S3 method for class 'model_fit'
axe_call(x, verbose = FALSE, ...)
# S3 method for class 'model_fit'
axe_ctrl(x, verbose = FALSE, ...)
# S3 method for class 'model_fit'
axe_data(x, verbose = FALSE, ...)
# S3 method for class 'model_fit'
axe_env(x, verbose = FALSE, ...)
# S3 method for class 'model_fit'
axe_fitted(x, verbose = FALSE, ...)Examples
library(parsnip)
library(rpart)
# Create model and fit
lm_fit <- linear_reg() |>
set_engine("lm") |>
fit(mpg ~ ., data = mtcars)
out <- butcher(lm_fit, verbose = TRUE)
#> ✔ Memory released: 1.56 MB
# Another parsnip model
gam_fit <- gen_additive_mod() |>
set_mode("regression") |>
fit(mpg ~ s(disp) + wt + gear, data = mtcars)
out <- butcher(gam_fit, verbose = TRUE)
#> ✔ Memory released: 1.62 MB
