How do you detect and fix multicollinearity?
IBMData Scientist · Technical Screen
Last updated
This question evaluates understanding of multicollinearity and related competencies in regression diagnostics, feature engineering, model interpretability, and the trade-offs between coefficient inference and predictive performance.
In a regression-style model (e.g., linear regression or logistic regression) you suspect multicollinearity among features.
- What is multicollinearity and why is it a problem?
- How would you detect it (diagnostics/plots/statistics)?
- How would you mitigate it in practice while preserving predictive performance and/or interpretability?
- How does the answer differ for inference (understanding coefficients) vs pure prediction?
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