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What happens k-fold validation?
Training data is divided into k equal sized subsets. Then, 1 subset is randomly selected and kept aside for validation, while the rest are used for training.
k random samples are picked and set aside to form the validation set, while the rest of the samples are used for training.
k random samples are picked and used for training, while the rest are used for validation.
k different models are built using the same training data, but with different hyperparameter settings and which are then validated against the test data. The best model is then chosen.
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