mlr3fselect.svm_rfe: SVM-RFE Callback

In mlr3fselect: Feature Selection for 'mlr3'

SVM-RFE Callback

Description

Runs a recursive feature elimination with a mlr3learners::LearnerClassifSVM. The SVM must be configured with type = "C-classification" and kernel = "linear".

Source

Guyon I, Weston J, Barnhill S, Vapnik V (2002). “Gene Selection for Cancer Classification using Support Vector Machines.” Machine Learning, 46(1), 389–422. ISSN 1573-0565, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1023/A:1012487302797")}.

Examples

clbk("mlr3fselect.svm_rfe")

library(mlr3learners)

# Create instance with classification svm with linear kernel
instance = fsi(
  task = tsk("sonar"),
  learner = lrn("classif.svm", type = "C-classification", kernel = "linear"),
  resampling = rsmp("cv", folds = 3),
  measures = msr("classif.ce"),
  terminator = trm("none"),
  callbacks = clbk("mlr3fselect.svm_rfe"),
  store_models = TRUE
)

fselector = fs("rfe", feature_number = 5, n_features = 10)

# Run recursive feature elimination on the Sonar data set
fselector$optimize(instance)

mlr3fselect documentation built on Oct. 30, 2024, 9:19 a.m.