K-Fold Cross-Validation Purpose

Easy

machine-learning Meta Google Microsoft

Multiple Choice

It trains the model 5 times faster than a single split It ensures every data point is used for both training and validation, reducing variance in the performance estimate It increases the size of the training set by 5x It eliminates the need for a held-out test set entirely

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