twofold_blocked_cross_validation: twofold_blocked_cross_validation

In bbuchsbaum/rMVPA: Multivoxel Pattern Analysis in R

twofold_blocked_cross_validation

Description

Construct a cross-validation specification that randomly partitions the input set into two sets of blocks.

Usage

twofold_blocked_cross_validation(block_var, nreps = 10)

Arguments

block_var	An integer vector representing the cross-validation blocks. Each block is indicated by a unique integer.
nreps	An integer specifying the number of repetitions for the twofold split.

Details

This function creates a cross-validation scheme for cases where data is organized into blocks, and these blocks are divided into two groups for evaluation. This approach can be useful when there is an inherent structure or dependency within the blocks, and separating them can help to avoid biased estimates of model performance. It returns an object of class "twofold_blocked_cross_validation", "cross_validation", and "list".

Value

An object of class "twofold_blocked_cross_validation", "cross_validation", and "list" containing the block_var, nfolds (fixed at 2 for this function), nreps, and block_ind.

Examples

blockvar <- rep(1:5, each=10)
nreps <- 5
cval <- twofold_blocked_cross_validation(blockvar, nreps=nreps)
samples <- crossval_samples(cval, as.data.frame(matrix(rnorm(50*50),50,50)), y=rep(letters[1:5],10))
stopifnot(nrow(samples) == nreps)

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