Practice Data Splitting Techniques - 12.3 | 12. Model Evaluation and Validation | Data Science Advance
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Data Splitting Techniques

12.3 - Data Splitting Techniques

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Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is Hold-Out Validation?

💡 Hint: Think about what happens to the data after splitting.

Question 2 Easy

Why is K-Fold Cross-Validation used?

💡 Hint: Consider the benefits of using multiple parts of the data.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the main purpose of data splitting techniques?

To increase data size
To evaluate model generalization
To remove noise from data

💡 Hint: Consider why you need to test a model's performance.

Question 2

True or False: K-Fold Cross-Validation can produce different outcomes based on the random selection of folds.

True
False

💡 Hint: Think about how random selection plays a role.

2 more questions available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Design a research experiment where you must use Nested Cross-Validation to avoid data leakage. Describe the dataset, the importance of both loops, and how you would proceed.

💡 Hint: Think through all data's roles and how they must interact without leakages.

Challenge 2 Hard

Evaluate a scenario where using Hold-Out Validation might lead to misleading conclusions. What could be the potential risks?

💡 Hint: Reflect on how a biased representation in your test set could impact final assessment.

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