AI engineering glossary · Feature engineering data prep
What is Yeo-Johnson transform?
Yeo-Johnson transform: An extension of the Box-Cox power transform that also works with zero and negative values. Like Box-Cox, it estimates a parameter from the data to make the feature more symmetric and normal-looking, making it a general-purpose choice.
Yeo-Johnson transform: an example
A profit column containing losses and gains, such as -5,000 to 80,000, can be Yeo-Johnson transformed, though Box-Cox would fail.
Related terms
More Feature engineering data prep terms
- ADASYN
- Aggregation feature
- ANOVA F-test
- Automated feature engineering
- Backward elimination
- Bag of words
- Binary encoding
- Boruta
Where you learn it
Yeo-Johnson 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.