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ML Academy

Classical ML

Interview question

  • seniorlevel
  • 15 minsuggested time
  • 2Data scientist, ML engineer

In a no-show model, the baggage-weight field is missing for 40% of high-risk-segment bookings and 5% of the rest (hypothetical). An analyst wants to drop rows with missing values; another wants to fill with the mean. How do you handle missing values, and what do you check?

Tests: Missing-data mechanisms (MCAR, MAR, MNAR), imputation and its effects on distributions and relationships, missingness indicators, and train-serve consistency.

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