generate.predictions.bssamples: Function to generate predictions on each sample
In janejkanske/SupaLarna: Package for the SuperLearner vs clincians study

View source: R/generate.predictions.bssamples.r

This makes predictions on the input samples using a prediciton function as parameter.

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generate.predictions.bssamples(samples,
  prediction_func = "predictions.with.superlearner", parallel = FALSE,
  n_cores = NULL, log = TRUE, boot = FALSE, write_to_disk = FALSE)

`samples`	Bootstrap samples as prepared by prep.bssamples. No default.
`prediction_func`	Name of function that generates predictions. Defaults to "predictions.with.superlearner"
`parallel`	Logical. If TRUE the training will be run in parallel. Defaults to FALSE.
`n_cores`	Integer. The number of cores to use for parallel computing. Defaults to NULL.
`log`	Logical. Passed to predictions.with.superlearner. If TRUE progress is logged in logfile. Defaults to TRUE.
`boot`	Logical. Passed to predictions.with.superlearner. Affects only what is printed to logfile. If TRUE prepped_sample is assumed to be a bootstrap sample. Defaults to FALSE.
`write_to_disk`	Logical. Passed to predictions.with.superlearner. If TRUE the prediction data is saved as RDS to disk. Defaults to FALSE