Practice The Structure Of A Decision Tree (5.1) - Supervised Learning - Classification Fundamentals (Weeks 6)
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The Structure of a Decision Tree

Practice - The Structure of a Decision Tree

Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is a root node in a Decision Tree?

💡 Hint: Think about the starting point of the Decision Tree.

Question 2 Easy

What do leaf nodes represent in a Decision Tree?

💡 Hint: Where do you end up after making all decisions?

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the primary goal of impurity measures in Decision Trees?

To increase complexity
To determine the best splits
To visualize the tree

💡 Hint: Consider why we'd use metrics like Gini impurity.

Question 2

True or False: Leaf nodes can represent decisions based on the majority class in a Decision Tree.

True
False

💡 Hint: Think about what happens at the end of the decision-making process.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Design a Decision Tree to classify animals based on features such as size, habitat, and diet. Discuss how you would approach the splitting and the considerations for impurities.

💡 Hint: Think about what features could lead to the most distinct classifications.

Challenge 2 Hard

You're given a dataset that can be heavily affected by noise. How would you ensure your Decision Tree model performs well on unseen data? What pruning techniques would you apply?

💡 Hint: Consider how tree depth can directly affect generalization.

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Reference links

Supplementary resources to enhance your learning experience.