Practice Local Interpretable Model Training (3.3.1.1.4) - Advanced ML Topics & Ethical Considerations (Weeks 14)
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Local Interpretable Model Training

Practice - Local Interpretable Model Training

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What does LIME stand for?

💡 Hint: Think about the focus of interpretability.

Question 2 Easy

Why is it important for AI models to be interpretable?

💡 Hint: Consider the stakeholders involved.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the main purpose of LIME?

To provide local explanations
To optimize model accuracy
To analyze global feature responses

💡 Hint: Think about its full name.

Question 2

SHAP is based on which theory?

Statistics
Game Theory
Machine Learning

💡 Hint: Consider what concept underpins fair attribution.

2 more questions available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Demonstrate how you would conduct a local interpretability analysis using LIME for a specific prediction in a healthcare model.

💡 Hint: Remember to consider a few features related to patient history.

Challenge 2 Hard

Imagine you are presenting a model to stakeholders who are concerned with fairness in predictions. How can you employ SHAP to address their concerns?

💡 Hint: Think about what questions stakeholders might have about fairness.

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Reference links

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