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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is Lasso regression?
💡 Hint: Think about how it modifies the loss function.
Question 2
Easy
Why is cross-validation important?
💡 Hint: Consider what could happen with just a single train/test split.
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 is the primary goal of Lasso regression?
- Maximize prediction accuracy
- Reduce overfitting through feature selection
- Increase model complexity
💡 Hint: Think about its impact on coefficients.
Question 2
True or False: Lasso regression can shrink coefficients to exactly zero.
- True
- False
💡 Hint: Consider its unique L1 penalty.
Solve and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
You have a dataset with 100 features to predict housing prices. Describe how you would implement Lasso regression to determine which features are most influential, including the surrogate steps.
💡 Hint: Consider how each step contributes to feature selection.
Question 2
Given an imbalanced dataset for classification, discuss how Stratified K-Fold cross-validation might improve your results compared to K-Fold in the context of a Lasso regression model.
💡 Hint: Reflect on the impact of class imbalance on model performance.
Challenge and get performance evaluation