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.
Usage
# 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.
Examples
library(kernlab)
#>
#> Attaching package: ‘kernlab’
#> The following object is masked from ‘package:ggplot2’:
#>
#> alpha
test <- gausspr(Species ~ ., data = iris, var = 2)
#> Using automatic sigma estimation (sigest) for RBF or laplace kernel
out <- butcher(test, verbose = TRUE)
#> ✔ Memory released: 2.30 kB
#> ✖ Disabled: `print()`, `summary()`, and `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: 3.10 kB
#> ✖ Disabled: `print()`, `summary()`, and `fitted()`
#> ✖ Could not add <butchered> class