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Reageer op: What is cross-validation and why is it important in machine learning?


Cross-validation is a technique used in machine learning to assess the performance of a predictive model. It involves splitting the data into multiple subsets, training the model on some of the subsets, and then testing it on the remaining subsets. This helps to ensure that the model is generalizing well to new, unseen data and can help prevent overfitting.