Practice Impurity Measures for Classification Trees - 5.3 | Module 3: Supervised Learning - Classification Fundamentals (Weeks 6) | Machine Learning
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5.3 - Impurity Measures for Classification Trees

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

Define Gini Impurity in your own words.

πŸ’‘ Hint: Think about how pure a group of items is.

Question 2

Easy

What does a Gini Impurity value of 0 mean?

πŸ’‘ Hint: Consider what it means when a group has no variety.

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 does a Gini Impurity value of 0 indicate?

  • True
  • False

πŸ’‘ Hint: Think about what 'pure' means.

Question 2

Is Information Gain a measure of the reduction in Gini Impurity?

  • Yes
  • No
  • Sometimes

πŸ’‘ Hint: Consider how Information Gain functions in splits.

Solve 2 more questions and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Given a dataset with three classes having equal distribution, how would you expect Gini Impurity to behave? Create a summary of your findings.

πŸ’‘ Hint: Consider how evenly distributed classes influence the outcome.

Question 2

Develop a decision tree using Gini impurity and assess its performance. What insights can be drawn from comparing with entropy-based splits?

πŸ’‘ Hint: Think about how the choice of impurity measures could affect learning and generalization.

Challenge and get performance evaluation