AI engineering glossary · Feature engineering data prep
What is quantile transform?
Quantile transform (also called QuantileTransformer, Rank transform): A transformation that maps a feature's values to their rank-based quantiles, so the result follows a chosen distribution, typically uniform or normal. It sharply reduces the effect of outliers and can straighten odd distributions, but it distorts distances between values.
Quantile transform: an example
Applying a uniform quantile transform to salaries makes the median salary 0.5 and the top 1 percent all lie between 0.99 and 1, regardless of how huge the maximum is.
Related terms
More Feature engineering data prep terms
- Rare category grouping
- Ratio feature
- Recursive feature elimination
- Robust scaling
- Rolling statistics
- Sample weights
- SMOTE
- Standardization
Where you learn it
Quantile transform is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.