How do I use stratified K-fold cross-validation?

What is stratified K-fold cross-validation?

Stratified K-fold cross-validation is a technique used to ensure that each fold of the dataset has the same proportion of classes as the entire dataset.

Why is stratified K-fold important?

It's important because it helps to maintain the distribution of classes, which is especially useful in imbalanced datasets.

How do I implement stratified K-fold in Python?

You can use the StratifiedKFold class from the sklearn.model_selection module. Here's a basic example:

from sklearn.model_selection import StratifiedKFold

skf = StratifiedKFold(n_splits=5)
for train_index, test_index in skf.split(X, y):
    X_train, X_test = X[train_index], X[test_index]
    y_train, y_test = y[train_index], y[test_index]