12.3.B - K-Fold Cross-Validation
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Practice Questions
Test your understanding with targeted questions
What is K-Fold Cross-Validation?
💡 Hint: Think about how we divide the data.
How many times does the model train in K-Fold Cross-Validation?
💡 Hint: Consider what happens to each fold.
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Interactive Quizzes
Quick quizzes to reinforce your learning
What is the purpose of K-Fold Cross-Validation?
💡 Hint: Consider what validation means in this context.
T/F: In K-Fold Cross-Validation, the same dataset is used for both training and testing.
💡 Hint: Think about how the folds are used.
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Challenge Problems
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Given a dataset of 500 samples, determine the implications of using K-Fold Cross-Validation with k = 20 versus k = 5. Discuss trade-offs.
💡 Hint: Contrast the sizes and diversity of training sets with different values of k.
How would K-Fold Cross-Validation change if the dataset was highly imbalanced? Outline your approach to modify K-Fold for such cases.
💡 Hint: Consider adjusting the way folds are created to account for class distributions.
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