AI engineering glossary · Feature engineering data prep
What is Box-Cox transform?
Box-Cox transform: A power transform that finds the exponent lambda, by maximum likelihood, that makes strictly positive data look most normal. With lambda = 0 it becomes the natural log; otherwise y = (x^lambda - 1) / lambda. It cannot handle zero or negative values.
Box-Cox transform: an example
Fitting Box-Cox on positive delivery times might choose lambda near 0.2, close to a log transform, and reduce right skew.
Related terms
More Feature engineering data prep terms
- Categorical variable
- Class imbalance
- Class weights
- Column transformer
- Constant feature
- Constant imputation
- Cook's distance
- Correlation filter
Where you learn it
Box-Cox 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.