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ksvm 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_ksvm class is not appended.

Usage

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

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

# S3 method for ksvm
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 ksvm object.

Examples

# \donttest{
# Load libraries
suppressWarnings(suppressMessages(library(parsnip)))
suppressWarnings(suppressMessages(library(kernlab)))

# Load data
data(spam)

# Create model and fit
ksvm_class <- svm_poly(mode = "classification") %>%
  set_engine("kernlab") %>%
  fit(type ~ ., data = spam)
#>  Setting default kernel parameters  

out <- butcher(ksvm_class, verbose = TRUE)
#>  No memory released. Do not butcher.
# }