Question 1 of 30
A data scientist is working on a classification problem with a highly imbalanced dataset where one class significantly outnumbers the other. They are considering different cross-validation techniques to evaluate their model\'s performance. Which cross-validation method would be most appropriate for ensuring that each fold reflects the class distribution of the entire dataset?
Stratified k-fold cross-validation
Random sampling cross-validation
Leave-one-out cross-validation
Simple k-fold cross-validation

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