fcv: Functional Cross-Validation mapping

In functionals: Functional Programming with Parallelism and Progress Tracking

Functional Cross-Validation mapping

Description

Applies a user-defined function '.f' to each element of '.splits', typically from cross-validation objects such as 'rsample::vfold_cv()'.

Usage

fcv(.splits, .f, ncores = NULL, pb = FALSE, ...)

Arguments

.splits	A list of resample splits (e.g., from 'rsample::vfold_cv()').
.f	A function to apply to each split. Typically expects a single 'split' object.
ncores	Integer. Number of cores to use for parallel processing. Default is 'NULL' (sequential).
pb	Logical. Whether to display a progress bar. Default is 'FALSE'.
...	Additional arguments passed to '.f'.

Value

A list of results returned by applying '.f' to each element of '.splits'.

Examples

if (requireNamespace("rsample", quietly = TRUE)) {
  set.seed(123)
  cv_splits <- rsample::vfold_cv(mtcars, v = 5)

  # Apply summary over training sets
  fcv(cv_splits$splits, function(split) {
    summary(rsample::analysis(split))
  })

  # With progress and parallel execution
  
    fcv(cv_splits$splits, function(split) {
      summary(rsample::analysis(split))
    }, ncores = 2, pb = TRUE)
  
}

functionals documentation built on Aug. 8, 2025, 7:32 p.m.