AI engineering glossary · Classical ML algorithms
What is VIF (variance inflation factor)?
Variance inflation factor (also called VIF): A score that measures how much a feature's weight variance is inflated because that feature can be predicted from the other features. It equals 1 / (1 - R^2), where R^2 comes from regressing that feature on the rest. Values above roughly 5 to 10 are commonly treated as a warning.
Variance inflation factor: an example
If income can be predicted from the other features with R^2 = 0.9, its score is 1 / (1 - 0.9) = 10, flagging heavy overlap.
Related terms
More Classical ML algorithms terms
- Voting classifier
- Weak learner
- XGBoost
- AdaBoost
- Agglomerative clustering
- Anomaly detection
- Apriori algorithm
- Association rule learning
Where you learn it
Variance inflation factor is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.