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2 cards from this section. Quick, good the night before a test.
What are the two main components of nested cross-validation?
Think about the concept of separating testing from training.
What is data leakage?
Consider scenarios where training may get wrongly influenced.
What is the main function of the outer loop in nested cross-validation?
Think about what happens when you measure a model's predictive ability.
True or False: Nested cross-validation prevents data leakage.
Recall the importance of separating testing from the training phase.
Create a nested cross-validation framework for a given dataset, including how to handle hyperparameter tuning, discussing the advantages and shortcomings.
Identify key belongings of hyperparameters that could impact predictions.
Analyze a model evaluation scenario where nested cross-validation wasn't used, and explain the possible implications and advantages had it been applied.
Reflect on what happens if tuning data leaks into performance metrics.
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