crossv_k: K-fold Cross-Validation Data Preparation

In bbuchsbaum/rMVPA: Multivoxel Pattern Analysis in R

K-fold Cross-Validation Data Preparation

Description

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)

bbuchsbaum/rMVPA documentation built on April 28, 2024, 6:30 a.m.