Stratified K-Fold Cross-Validation on Grouped Datasets

This article explains how to use optimization to perform stratified K-Fold cross-validation on a grouped dataset

Cross-validation is a common resampling technique to get more mileage from your dataset. The procedure involves taking repeated independent samples from the original dataset and fitting them to the desired model. Cross-validation is helpful for model selection, as it provides better generalization performance estimates than the holdout method. The resampling process ensures that we reap the benefits …

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