Generic cross-validation engine

For each fold (train/test indices):

1. Subset data[train, ]

2. Fit a model with .fit_fun(train_data, ...)

3. Evaluate with .measure_fun(model, test_data, ...)

Usage

cv_generic(
  data,
  folds,
  .fit_fun,
  .measure_fun,
  fit_args = list(),
  measure_args = list(),
  backend = c("serial", "future"),
  ...
)

Arguments

data

A matrix or data.frame of shape (n x p).

folds

A list of folds, each a list with $train and $test.

.fit_fun

Function: signature function(train_data, ...){}. Returns a fitted model.

.measure_fun

Function: signature function(model, test_data, ...){}. Returns a tibble or named list/vector of metrics.

fit_args

A list of additional named arguments passed to .fit_fun.

measure_args

A list of additional named arguments passed to .measure_fun.

backend

Character string: "serial" (default) or "future" for parallel execution using the future framework.

...

Currently ignored (arguments should be passed via fit_args or measure_args).

Value

A tibble with columns:

fold

integer fold index

model

list of fitted models

metrics

list of metric tibbles/lists