Practice Marginal Contribution Calculation - 3.3.2.1.2 | Module 7: Advanced ML Topics & Ethical Considerations (Weeks 14) | Machine Learning
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3.3.2.1.2 - Marginal Contribution Calculation

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What are Shapley values used for?

πŸ’‘ Hint: Think about the fairness in assigning credit to features.

Question 2

Easy

Define marginal contribution in your own words.

πŸ’‘ Hint: What happens when you add a feature to a set?

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 do Shapley values help with in machine learning?

  • A) Increasing accuracy
  • B) Distributing feature contributions
  • C) Reducing data size

πŸ’‘ Hint: Consider how different features interact.

Question 2

True or False: Marginal contributions take into account only the last feature added.

  • True
  • False

πŸ’‘ Hint: Think about combinations of features.

Solve and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Suppose you have a machine learning model predicting house prices based on features like size, neighborhood, and age. Explain how you'd set up a Shapley value calculation for a new property and what information you'd derive from it.

πŸ’‘ Hint: Utilize combinations of features to analyze contribution.

Question 2

Illustrate how marginal contribution calculations might differ between a linear and non-linear model. What are the implications for feature interactions?

πŸ’‘ Hint: Consider the types of relationships in your models.

Challenge and get performance evaluation