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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is the main purpose of time-series cross-validation?
💡 Hint: Think about why the order of data matters.
Question 2
Easy
Name one technique used in time-series cross-validation.
💡 Hint: Remember we discussed a couple of methods.
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 main benefit of time-series cross-validation?
- It randomizes data splits
- It prevents future data from influencing training
- It allows for larger datasets in training
💡 Hint: Think about what is unique about time-series data.
Question 2
True or False: In rolling window validation, the training set size increases with each iteration.
- True
- False
💡 Hint: Reflect on how the training set evolves.
Solve and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
You have a dataset of monthly sales over five years and need to forecast future sales using both rolling and expanding techniques. Design an evaluation strategy for both.
💡 Hint: Think about the practical implications of each method.
Question 2
Critique a model that relied solely on rolling methods in an unstable market context. What issues might arise?
💡 Hint: Consider the nature of the dataset.
Challenge and get performance evaluation