Axing an multnet. — axe-multnet • butcher

multnet objects are created from carrying out multinomial regression in the glmnet package.

Usage

# S3 method for multnet
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 multnet object.

Examples

# Load libraries
library(parsnip)

# Load data
set.seed(1234)
predictrs <- matrix(rnorm(100*20), ncol = 20)
colnames(predictrs) <- paste0("a", seq_len(ncol(predictrs)))
response <- as.factor(sample(1:4, 100, replace = TRUE))

# Create model and fit
multnet_fit <- multinom_reg(penalty = 0.1) %>%
  set_engine("glmnet") %>%
  fit_xy(x = predictrs, y = response)

out <- butcher(multnet_fit, verbose = TRUE)
#> ✔ Memory released: 128 B