gausspr objects are created from kernlab package, which provides a means to do classification, regression, clustering, novelty detection, quantile regression and dimensionality reduction. Since fitted model objects from kernlab are S4, the butcher_gausspr class is not appended.

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

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

# S3 method for gausspr
axe_env(x, verbose = FALSE, ...)

# S3 method for gausspr
axe_fitted(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 gausspr object.

Examples

suppressWarnings(suppressMessages(library(kernlab))) test <- gausspr(Species ~ ., data = iris, var = 2)
#> Using automatic sigma estimation (sigest) for RBF or laplace kernel
out <- butcher(test, verbose = TRUE)
#> Memory released: '1,960 B'
#> Disabled: `print()`, `summary()`, `fitted()`
#> Could not add 'butchered' class
# Example with simulated regression data x <- seq(-20, 20, 0.1) y <- sin(x)/x + rnorm(401, sd = 0.03) test2 <- gausspr(x, y)
#> Using automatic sigma estimation (sigest) for RBF or laplace kernel
out <- butcher(test2, verbose = TRUE)
#> Memory released: '3,104 B'
#> Disabled: `print()`, `summary()`, `fitted()`
#> Could not add 'butchered' class