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.
Examples
# Load libraries
library(parsnip)
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)
#> ✖ The butchered object is 2.32 kB larger than the original. Do not butcher.