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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is post-pruning?
💡 Hint: Think about the purpose of enhancing model performance.
Question 2
Easy
What does overfitting refer to?
💡 Hint: Consider what happens when a model learns too many details.
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 purpose of post-pruning?
- To increase tree complexity
- To remove unnecessary branches
- To speed up training time
💡 Hint: Think about how to simplify a complex model.
Question 2
True or False: Overfitting occurs when a model is too simple.
- True
- False
💡 Hint: Remember what happens with too much detail.
Solve 2 more questions and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Given a scenario where a Decision Tree has a total of 10 branches with varying importance, how would you determine which branches to prune without significantly losing predictive accuracy?
💡 Hint: Consider the relationship between branches and overall model performance.
Question 2
Describe the implications of using a small validation set in post-pruning. What risks does this pose?
💡 Hint: Think about why sample size matters in making statistical decisions.
Challenge and get performance evaluation