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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is K-Fold Cross-Validation?
💡 Hint: Think about how we divide the data.
Question 2
Easy
How many times does the model train in K-Fold Cross-Validation?
💡 Hint: Consider what happens to each fold.
Practice 4 more questions and get performance evaluation
Interactive Quizzes
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What is the purpose of K-Fold Cross-Validation?
- To reduce model complexity
- To validate model performance
- To eliminate bias completely
💡 Hint: Consider what validation means in this context.
Question 2
T/F: In K-Fold Cross-Validation, the same dataset is used for both training and testing.
- True
- False
💡 Hint: Think about how the folds are used.
Solve and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
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.
Question 2
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.
Challenge and get performance evaluation