Explain why LASSO selects features

Q: Explain why LASSO selects features

This is a Machine Learning interview question from Meta for Data Scientist roles. View the full question and solution on PracHub.

Q: How do I approach Machine Learning interview questions?

Machine Learning questions require understanding of core concepts and practice. PracHub provides solutions with explanations to help you master machine learning interviews.

Question

Explain why LASSO performs feature selection. Provide: 1) high-level intuition comparing L1 vs. L2 penalties; 2) geometric interpretation of the constraint region and why coefficients hit exact zero; 3) the KKT/subgradient condition for when a coefficient becomes zero; 4) the effect of correlated predictors on selection stability; 5) why standardization matters and what happens if you omit it; 6) how lambda is chosen and how it shifts bias–variance; 7) when Elastic Net is preferable and why.

Explain why LASSO selects features

Comments (0)