Practice - Pruning and Overfitting
Practice Questions
Test your understanding with targeted questions
Define overfitting in your own words.
💡 Hint: Think about how a student might memorize answers without understanding.
What is pruning?
💡 Hint: Consider how gardeners trim plants.
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Interactive Quizzes
Quick quizzes to reinforce your learning
What is overfitting?
💡 Hint: Think about the consequence of too much learning from data.
True or False: Pruning can lead to a decrease in training accuracy.
💡 Hint: Remember, pruning reduces complexity.
1 more question available
Challenge Problems
Push your limits with advanced challenges
Consider a dataset where you notice your decision tree is performing excellently on training data but poorly on validation data. How would you approach pruning, and what steps would you take?
💡 Hint: Consult performance metrics to inform your pruning decisions.
Imagine you have a decision tree with many splits leading to small, specific rules to classify data. How can pre-pruning aid in improving the model's generalization?
💡 Hint: Think about how stopping growth early can impact complexity.
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Reference links
Supplementary resources to enhance your learning experience.