What is skewness correction in feature engineering?
Updated May 16, 2026
Short answer
Skewness correction transforms highly skewed data into more symmetric distributions.
Deep explanation
Skewed data can negatively affect model performance. Transformations like log, square root, and Box-Cox help normalize distributions and improve model stability.
Real-world example
Used in insurance claim prediction where claim amounts are highly skewed.
Common mistakes
- Applying transformations without checking distribution first.
Follow-up questions
- What is positive vs negative skew?
- What is Box-Cox transformation?