*_bagg objects are created from the ipred package, which
is used for bagging classification, regression and survival trees.
Usage
# S3 method for regbagg
axe_call(x, verbose = FALSE, ...)
# S3 method for classbagg
axe_call(x, verbose = FALSE, ...)
# S3 method for survbagg
axe_call(x, verbose = FALSE, ...)
# S3 method for regbagg
axe_ctrl(x, verbose = FALSE, ...)
# S3 method for classbagg
axe_ctrl(x, verbose = FALSE, ...)
# S3 method for survbagg
axe_ctrl(x, verbose = FALSE, ...)
# S3 method for regbagg
axe_data(x, verbose = FALSE, ...)
# S3 method for classbagg
axe_data(x, verbose = FALSE, ...)
# S3 method for survbagg
axe_data(x, verbose = FALSE, ...)
# S3 method for regbagg
axe_env(x, verbose = FALSE, ...)
# S3 method for classbagg
axe_env(x, verbose = FALSE, ...)
# S3 method for survbagg
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.
Examples
library(ipred)
fit_mod <- function() {
boop <- runif(1e6)
bagging(y ~ x, data.frame(y = rnorm(1e4), x = rnorm(1e4)))
}
mod_fit <- fit_mod()
mod_res <- butcher(mod_fit)
weigh(mod_fit)
#> # A tibble: 705 × 2
#> object size
#> <chr> <dbl>
#> 1 mtrees.btree.terms 20.4
#> 2 mtrees.btree.terms 20.4
#> 3 mtrees.btree.terms 20.4
#> 4 mtrees.btree.terms 20.4
#> 5 mtrees.btree.terms 20.4
#> 6 mtrees.btree.terms 20.4
#> 7 mtrees.btree.terms 20.4
#> 8 mtrees.btree.terms 20.4
#> 9 mtrees.btree.terms 20.4
#> 10 mtrees.btree.terms 20.4
#> # ℹ 695 more rows
weigh(mod_res)
#> # A tibble: 480 × 2
#> object size
#> <chr> <dbl>
#> 1 mtrees.btree.where 0.680
#> 2 mtrees.btree.where 0.680
#> 3 mtrees.btree.where 0.680
#> 4 mtrees.btree.where 0.680
#> 5 mtrees.btree.where 0.680
#> 6 mtrees.btree.where 0.680
#> 7 mtrees.btree.where 0.680
#> 8 mtrees.btree.where 0.680
#> 9 mtrees.btree.where 0.680
#> 10 mtrees.btree.where 0.680
#> # ℹ 470 more rows