SL_stabs_fitfun {flevr} | R Documentation |
Wrapper for using Super Learner-based extrinsic selection within stability selection
Description
A wrapper function for Super Learner-based extrinsic variable selection within
stability selection, using the stabs
package.
Usage
SL_stabs_fitfun(x, y, q, ...)
Arguments
x |
the features. |
y |
the outcome of interest. |
q |
the number of features to select on average. |
... |
other arguments to pass to |
Value
a named list, with elements: selected
(a logical vector
indicating whether or not each variable was selected); and path
(
a logical matrix indicating which variable was selected at each step).
See Also
stabsel
for general usage of stability selection.
Examples
data("biomarkers")
# subset to complete cases for illustration
cc <- complete.cases(biomarkers)
dat_cc <- biomarkers[cc, ]
# use only the mucinous outcome, not the high-malignancy outcome
y <- dat_cc$mucinous
x <- dat_cc[, !(names(dat_cc) %in% c("mucinous", "high_malignancy"))]
feature_nms <- names(x)
# use stability selection with SL (using small number of folds for CV,
# small SL library and small number of bootstrap replicates for illustration only)
set.seed(20231129)
library("SuperLearner")
sl_stabs <- stabs::stabsel(x = x, y = y,
fitfun = SL_stabs_fitfun,
args.fitfun = list(SL.library = "SL.glm", cvControl = list(V = 2)),
q = 2, B = 5, PFER = 5)
sl_stabs
[Package flevr version 0.0.4 Index]