dot-fit_super_learner: Fit a stacked super learner ensemble
In misl: Multiple Imputation by Super Learning
.fit_super_learner R Documentation
Fit a stacked super learner ensemble
Description
Fit a stacked super learner ensemble
Usage
.fit_super_learner(
train_data,
full_data,
xvars,
yvar,
outcome_type,
learner_names,
cv_folds = 5
)
Arguments
cv_folds
Integer number of cross-validation folds used when stacking
multiple learners. Ignored when only a single learner is supplied.
Value
Named list with $boot (fit on bootstrap sample) and
$full (fit on full observed data; NULL unless continuous).
misl documentation built on April 8, 2026, 9:07 a.m.
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| .fit_super_learner | R Documentation |
Fit a stacked super learner ensemble
Description
Fit a stacked super learner ensemble
Usage
.fit_super_learner(
train_data,
full_data,
xvars,
yvar,
outcome_type,
learner_names,
cv_folds = 5
)
Arguments
cv_folds |
Integer number of cross-validation folds used when stacking multiple learners. Ignored when only a single learner is supplied. |
Value
Named list with $boot (fit on bootstrap sample) and
$full (fit on full observed data; NULL unless continuous).
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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