BORG (version 0.2.5)

borg_vfold_cv: BORG-Guarded vfold_cv

Description

A guarded version of rsample::vfold_cv() that checks for data dependencies before creating folds. If spatial, temporal, or clustered dependencies are detected, random CV is blocked.

Usage

borg_vfold_cv(
  data,
  v = 10,
  repeats = 1,
  strata = NULL,
  coords = NULL,
  time = NULL,
  groups = NULL,
  target = NULL,
  allow_override = FALSE,
  auto_block = FALSE,
  ...
)

Value

If no dependencies detected or allow_override = TRUE, returns an rset object from rsample. If dependencies detected and auto_block = TRUE, returns BORG-generated blocked CV folds.

Arguments

data

A data frame.

v

Integer. Number of folds. Default: 10.

repeats

Integer. Number of repeats. Default: 1.

strata

Character. Column name for stratification.

coords

Character vector of length 2. Coordinate columns for spatial check.

time

Character. Time column for temporal check.

groups

Character. Group column for clustered check.

target

Character. Target variable for dependency detection.

allow_override

Logical. If TRUE, allow random CV with explicit confirmation. Default: FALSE.

auto_block

Logical. If TRUE, automatically switch to blocked CV when dependencies detected. If FALSE, throw error. Default: FALSE.

...

Additional arguments passed to rsample::vfold_cv().

See Also

borg_cv for direct blocked CV generation.

Examples

# \donttest{
if (requireNamespace("rsample", quietly = TRUE)) {
  # Safe: no dependencies
  data <- data.frame(x = rnorm(100), y = rnorm(100))
  folds <- borg_vfold_cv(data, v = 5)

  # Use auto_block to automatically switch to spatial CV:
  spatial_data <- data.frame(
    lon = runif(100, -10, 10),
    lat = runif(100, -10, 10),
    response = rnorm(100)
  )
  folds <- borg_vfold_cv(spatial_data, coords = c("lon", "lat"),
                         target = "response", auto_block = TRUE)
}
# }