Instruction: Explain what cross-validation is and why it is useful.
Context: This question tests the candidate's knowledge of techniques used to assess the effectiveness of machine learning models, specifically to avoid overfitting.
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The way I'd think about it is this: I use cross-validation when I want a more reliable estimate of model performance than a single train-validation split can give me. By training and evaluating across multiple folds, I get a better sense of whether the result is stable or just...