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Axing a rpart.

Source: R/rpart.R
axe-rpart.Rd

rpart objects are created from the rpart package, which is used for recursive partitioning for classification, regression and survival trees.

Usage

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

# S3 method for rpart
axe_ctrl(x, verbose = FALSE, ...)

# S3 method for rpart
axe_data(x, verbose = FALSE, ...)

# S3 method for rpart
axe_env(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 rpart object.

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