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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
Define overfitting in the context of Decision Trees.
💡 Hint: Think about how memorization differs from understanding.
Question 2
Easy
What is pruning in Decision Trees?
💡 Hint: Consider how trimming a tree helps keep it manageable.
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 overfitting in Decision Trees?
- Model learning the training data too well
- Model generalizing well
- Model being too simplistic
💡 Hint: Consider how well the model performs on new data.
Question 2
True or False: Pre-pruning only occurs after a decision tree is fully grown.
- True
- False
💡 Hint: Think about when the decision to stop growing the tree is made.
Solve 2 more questions and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
You have a dataset with many outliers. Discuss how you would use Decision Trees and pruning techniques to develop a predictive model while minimizing overfitting.
💡 Hint: Consider how pruning can balance bias and variance while dealing with complex datasets.
Question 2
Create a scenario where a Decision Tree fails due to overfitting, detailing how applying both pre-pruning and post-pruning could help rectify the issue.
💡 Hint: Reflect on how noise affects splits and how pruning might correct excessive complexity.
Challenge and get performance evaluation