crossv_block: Block Cross-Validation Data Preparation

In bbuchsbaum/rMVPA: Multivoxel Pattern Analysis in R

Block Cross-Validation Data Preparation

Description

This function prepares the data for block cross-validation by dividing the dataset based on the provided block variable. It creates subsets of training and testing data for each block without performing any analysis or fitting models.

Usage

crossv_block(data, y, block_var, id = ".id")

Arguments

data	A data frame containing the training data.
y	A response vector.
block_var	An integer vector defining the cross-validation blocks.
id	A character string specifying the identifier for the output data frame.

Value

A tibble containing the training and testing data, response vectors, and block IDs for each fold.

Examples

X <- data.frame(x1 = rnorm(100), x2 = rnorm(100))
y <- rep(letters[1:4], 25)
block_var <- rep(1:4, each = 25)
cv <- crossv_block(X, y, block_var)

bbuchsbaum/rMVPA documentation built on April 23, 2024, 7:35 a.m.