Practice Feature Importance (Understanding What Matters to the Model) - 4.3.3 | Module 4: Advanced Supervised Learning & Evaluation (Weeks 7) | Machine Learning
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Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What does feature importance indicate?

πŸ’‘ Hint: Consider how helpful a feature is for making predictions.

Question 2

Easy

What is Gini impurity used for?

πŸ’‘ Hint: Think about what happens when you split data into groups.

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 feature importance measure?

  • The overall accuracy of the model
  • The contribution of each feature to model predictions
  • The number of trees in the forest

πŸ’‘ Hint: Consider what feature importance calculates.

Question 2

True or False: Impurity measures are used to calculate feature importance.

  • True
  • False

πŸ’‘ Hint: Think about how trees evaluate their splits.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Given a dataset, explain how you would use feature importance scores to optimize your model.

πŸ’‘ Hint: Think about the role of features in both model performance and understanding.

Question 2

Discuss how changes in data distribution may affect feature importance and what you would do in such scenarios.

πŸ’‘ Hint: Consider features as dynamic elements that can evolve with data.

Challenge and get performance evaluation