A guarded version of caret::trainControl() that validates CV settings
against data dependencies.
Usage
borg_trainControl(
data,
method = "cv",
number = 10,
coords = NULL,
time = NULL,
groups = NULL,
target = NULL,
allow_override = FALSE,
...
)Arguments
- data
A data frame. Required for dependency checking.
- method
Character. Resampling method.
- number
Integer. Number of folds or iterations.
- coords
Character vector. Coordinate columns for spatial check.
- time
Character. Time column for temporal check.
- groups
Character. Group column for clustered check.
- target
Character. Target variable.
- allow_override
Logical. Allow random CV despite dependencies.
- ...
Additional arguments passed to
caret::trainControl().
Examples
# \donttest{
if (requireNamespace("caret", quietly = TRUE)) {
spatial_data <- data.frame(
lon = runif(50), lat = runif(50), response = rnorm(50)
)
ctrl <- borg_trainControl(
data = spatial_data,
method = "cv",
number = 5,
coords = c("lon", "lat")
)
}
# }