What is stratified k-fold validation?

What is stratified k-fold validation?

Stratified k-fold validation is a technique used in machine learning to ensure that each fold of the dataset has the same proportion of classes as the entire dataset.

Why is it important to use stratified k-fold validation?

It's important because it helps to reduce bias and variance in the model evaluation, especially in imbalanced datasets.

How does it differ from regular k-fold validation?

In regular k-fold validation, the data is split randomly, which can lead to imbalanced class distributions in some folds. Stratified k-fold maintains the class distribution.

Can you give me an example of how to implement it in Python?

Sure! You can use the StratifiedKFold class from the sklearn.model_selection module to implement it easily.