stratified_foldid: Build class-stratified cross-validation fold assignments

In xplus: Positive and Unlabeled Learning from Unbalanced Cases and Sparse Structures

Build class-stratified cross-validation fold assignments

Description

Assigns each observation to one of nfolds folds so that both classes are spread as evenly as possible across folds. This prevents a small class from being concentrated in a single fold, which would leave a cross-validation training split with fewer than the two observations per class that glmnet::glmnet() requires for binomial fits.

Usage

stratified_foldid(y, nfolds)

Arguments

y	Binary (0/1) vector of class labels.
nfolds	Number of folds.

Value

Integer vector of fold assignments in 1:nfolds, the same length as y, suitable for the foldid argument of glmnet::cv.glmnet().

xplus documentation built on Sept. 26, 2026, 5:07 p.m.