AI engineering glossary · Feature engineering data prep
What is boruta?
Boruta: A feature selection algorithm built around random forests. It adds shuffled 'shadow' copies of features and keeps only real features that repeatedly beat the best shadow feature in importance, giving a statistically grounded all-relevant selection.
Boruta: an example
A real column that never beats the best shuffled shadow column across many rounds is rejected as no better than noise.
Related terms
More Feature engineering data prep terms
- Box-Cox transform
- Categorical variable
- Class imbalance
- Class weights
- Column transformer
- Constant feature
- Constant imputation
- Cook's distance
Where you learn it
Boruta is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.