Regarding splitting datasets into training, validation, and test partitions, which ofthe following statements is true, if any?(i) The validation set is used multiple times to choose the best value forhyperparameters.(ii) The test set is used only once to determine the performance on unseen data.(iii) Improving performance on the validation set always improves performance onthe test set.
Question
Regarding splitting datasets into training, validation, and test partitions, which ofthe following statements is true, if any?(i) The validation set is used multiple times to choose the best value forhyperparameters.(ii) The test set is used only once to determine the performance on unseen data.(iii) Improving performance on the validation set always improves performance onthe test set.
Solution
(i) True - The validation set is used multiple times to tune the model's hyperparameters. This is because we want to adjust our model based on the validation set to prevent overfitting on the training data.
(ii) True - The test set is used only once to evaluate the model's performance on unseen data. This is to get an unbiased estimate of the model's performance, as it should not have any influence on the training process.
(iii) False - Improving performance on the validation set does not always improve performance on the test set. This is because the model may overfit to the validation set, which can lead to poor performance on the test set. This situation is often referred to as overfitting on the validation set.
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