After a fairly long life on GitHub, my R package, cvms, for cross-validating linear and logistic regression, is finally on CRAN!
With a few additions in the past months, this is a good time to catch you all up on the included functionality. For examples, check out the readme on GitHub!
The main purpose of cvms is to allow researchers to quickly compare their models with cross-validation, with a tidy output containing the relevant metrics.
I have spent the last couple of days adding functionality for performing repeated cross-validation to cvms and groupdata2. In this quick post I will show an example.
In cross-validation, we split our training set into a number (often denoted “k”) of groups called folds. We repeatedly train our machine learning model on k-1 folds and test it on the last fold, such that each fold becomes test set once. Then we average the results and celebrate with food and music.