cv_generic: Generic cross-validation engine

In bbuchsbaum/multivarious: Extensible Data Structures for Multivariate Analysis

Generic cross-validation engine

Description

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

bbuchsbaum/multivarious documentation built on July 16, 2025, 11:04 p.m.