twofold_blocked_cross_validation
twofold_blocked_cross_validation.RdConstruct a cross-validation specification that randomly partitions the input set into two sets of blocks.
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.
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.
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".
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)