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Compare Regularization Techniques and Their Use Cases

AmazonData Scientist · Technical Screen
MediumData ScientistTechnical ScreenMachine Learning

Last updated

Evaluates model evaluation, regularization, and regression basics for predictive analytics. Strong answers define precision and recall, compare L1, L2, L0, and L-infinity penalties, state OLS assumptions, and contrast linear and logistic regression formulas and losses.

Scenario

Model evaluation and regularization choices in predictive analytics.

Question

Define precision and recall; when is each more important? Compare L1, L2, L0, and L-infinity regularization and give use cases. List the key assumptions of linear regression. Write the formulas for logistic regression and linear regression and contrast them.

Hints

Mention sparsity, overfitting control, and link functions.