classbagg objects are created from the ipred package, which leverages various resampling and bagging techniques to improve predictive models.
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(ipred)
library(rpart)
library(MASS)
# Load data
data("GlaucomaM", package = "TH.data")
classbagg_fit <- bagging(Class ~ ., data = GlaucomaM, coob = TRUE)
out <- butcher(classbagg_fit, verbose = TRUE)
#> ✔ Memory released: "2.88 MB"
#> ✖ Disabled: `print()` and `summary()`
# Fit another model
data("DLBCL", package = "ipred")
mod <- bagging(Gene.Expression ~ MGEc.1 + MGEc.2 + MGEc.3 + MGEc.4 + IPI,
data = DLBCL,
coob = TRUE)
out <- butcher(mod, verbose = TRUE)
#> ✔ Memory released: "4.46 MB"
#> ✖ Disabled: `print()` and `summary()`