Answer / Anurag Kumar Tripathi

Cross-validation is a technique used in machine learning to evaluate model performance and prevent overfitting. It involves dividing the dataset into multiple subsets (or folds) and training and testing the model on different combinations of these subsets. The average performance across all runs provides a more reliable estimate of the model's generalization ability compared to training and testing on the same data.

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