rpart objects are created from the rpart package, which is used for recursive partitioning for classification, regression and survival trees.
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.
Examples
# Load libraries
library(parsnip)
library(rsample)
library(rpart)
# Load data
set.seed(1234)
split <- initial_split(mtcars, prop = 9/10)
car_train <- training(split)
# Create model and fit
rpart_fit <- decision_tree(mode = "regression") %>%
set_engine("rpart") %>%
fit(mpg ~ ., data = car_train, minsplit = 5, cp = 0.1)
out <- butcher(rpart_fit, verbose = TRUE)
#> ✔ Memory released: 17.62 kB
# Another rpart object
wrapped_rpart <- function() {
some_junk_in_environment <- runif(1e6)
fit <- rpart(Kyphosis ~ Age + Number + Start,
data = kyphosis,
x = TRUE, y = TRUE)
return(fit)
}
# Remove junk
cleaned_rpart <- axe_env(wrapped_rpart(), verbose = TRUE)
#> ✔ Memory released: 8.06 MB
# Check size
lobstr::obj_size(cleaned_rpart)
#> 53.42 kB