extract_sampled_split_predictions: Extract sampled-split predictions from a CV.SuperLearner...

Description Usage Arguments Value See Also

View source: R/extract_sampled_split_predictions.R

Description

Use the cross-validated Super Learner and a set of specified sample-splitting folds to extract cross-fitted predictions on separate splits of the data. This is primarily for use in cases where you have already fit a CV.SuperLearner and want to use the fitted values to compute variable importance without having to re-fit. The number of folds used in the CV.SuperLearner must be even.

Usage

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extract_sampled_split_predictions(
  cvsl_obj = NULL,
  sample_splitting = TRUE,
  sample_splitting_folds = NULL,
  full = TRUE
)

Arguments

cvsl_obj

An object of class "CV.SuperLearner"

sample_splitting

logical; should we use sample-splitting or not? Defaults to TRUE.

sample_splitting_folds

A vector of folds to use for sample splitting

full

logical; is this the fit to all covariates (TRUE) or not (FALSE)?

Value

The predictions on validation data in each split-sample fold; a list of length two, each element of which is a list with the predictions on the split-sample cross-validation data.

See Also

CV.SuperLearner for usage of the CV.SuperLearner function.


vimp documentation built on Aug. 16, 2021, 5:08 p.m.