Handle imbalance, sampling, and overfitting
Company: LinkedIn
Role: Data Scientist
Category: Machine Learning
Difficulty: easy
Interview Round: Technical Screen
Overview: This question evaluates a data scientist's proficiency in machine learning topics including handling class imbalance, selecting and interpreting evaluation metrics, verifying sample representativeness, preventing overfitting in tree-based models, and understanding why L1/L2 regularization introduces biased coefficient estimates.
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