AI engineering glossary · Feature engineering data prep
What is ANOVA F-test?
ANOVA F-test (also called F-classif): A statistical test that compares group means to decide whether a numeric feature differs across the classes of a categorical target. As a filter method it ranks numeric features by F-value, where higher values mean stronger separation.
ANOVA F-test: an example
Comparing average income across 'default' and 'no default' groups gives an F-score used to rank income against other numeric features.
Related terms
More Feature engineering data prep terms
- Automated feature engineering
- Backward elimination
- Bag of words
- Binary encoding
- Boruta
- Box-Cox transform
- Categorical variable
- Class imbalance
Where you learn it
ANOVA F-test is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.