Practice Pruning Strategies: Taming The Tree's Growth (5.5) - Supervised Learning - Classification Fundamentals (Weeks 6)
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Pruning Strategies: Taming the Tree's Growth

Practice - Pruning Strategies: Taming the Tree's Growth

Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is pruning in Decision Trees?

💡 Hint: Think about reducing complexity.

Question 2 Easy

Name one parameter used in pre-pruning.

💡 Hint: It's related to limiting tree growth.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the goal of pruning a Decision Tree?

Increase complexity
Reduce overfitting
Add branches

💡 Hint: Think about what pruning achieves.

Question 2

True or False: Pre-pruning means pruning a tree after it has fully grown.

True
False

💡 Hint: Consider the sequence of events.

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Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

You are given a highly complex Decision Tree that is performing poorly on validation data. Outline a comprehensive strategy using both pre-pruning and post-pruning methods to improve this model.

💡 Hint: Consider both aspects: limitations during growth and adjustments afterward.

Challenge 2 Hard

Design a scenario where pre-pruning could lead to underfitting and suggest how to detect and avoid this problem during model building.

💡 Hint: Reflect on parameter settings and training results.

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Reference links

Supplementary resources to enhance your learning experience.