This function prepares the data for k-fold cross-validation by dividing the
dataset into k folds. It creates subsets of training and testing data for
each fold without performing any analysis or fitting models.
Usage
crossv_k(data, y, k = 5, id = ".id")
Arguments
- data
A data frame containing the training data.
- y
A response vector.
- k
An integer specifying the number of folds for cross-validation.
- id
A character string specifying the identifier for the output data frame.
Value
A tibble containing the training and testing data, response vectors, and fold IDs for each fold.
Examples
data <- iris[,-5]
y <- iris$Species
result <- crossv_k(data, y, k = 5)