How do you determine which features are important for your model?

Machine Learning
Hard
Amazon
83.7K views

Direct Answer

Tests feature engineering knowledge and the ability to select relevant variables to improve model efficiency and interpretability.

Why Interviewers Ask This

Irrelevant features add noise and computational cost. Interviewers want to see if you can identify signal from noise using statistical methods or model-based importance scores.

How to Answer This Question

Discuss correlation analysis, mutual information, and permutation importance. Mention tree-based models like Random Forest for feature importance. Explain the iterative process of feature selection and re-evaluation.

Key Points to Cover

  • Check for multicollinearity
  • Use model-based importance scores
  • Iterative refinement process

Sample Answer

I start by analyzing correlations to remove redundant features. Then, I use model-based importance scores from Random Forests or Gradient Boosting to rank features. Permutation importance helps validate which features ac…

Common Mistakes to Avoid

  • Selecting features arbitrarily
  • Ignoring domain knowledge
  • Using only p-values without context

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