AI engineering glossary · Feature engineering data prep
What is stepwise selection?
Stepwise selection: A family of greedy feature selection procedures that add or remove one variable at a time based on a criterion such as p-value, AIC or cross-validated score, sometimes allowing both moves in the same run. It is quick but can overfit and is unstable.
Stepwise selection: an example
Starting from an empty regression, add the best predictor, then check whether any earlier variable should now be dropped, and repeat until AIC stops improving.
Related terms
More Feature engineering data prep terms
- Stop words
- Target encoding
- Text preprocessing
- Threshold tuning
- Tomek links
- Training-serving skew
- Undersampling
- Unit vector scaling
Where you learn it
Stepwise selection is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.