We use the cross_val_score() function from sklearn to perform cross-validation. It performs K-fold cross-validation.
What it does is that it splits our dataset into k distinct subsets also called folds. Then it trains and evaluates our model k times, picking a different subset for evaluation and using the rest of the k-1 subsets for training. The result is an array containing k evaluation scores.
So, cross-validation, when k is 5, looks like:
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