AI engineering glossary · Feature engineering data prep
What is cook's distance?
Cook's distance: A measure of how much a regression's fitted values change when a single observation is removed. Large values flag points with strong influence on the model, combining how extreme the point is in features and how far it lies from the fit.
Cook's distance: an example
A point with Cook's distance far larger than the rest could shift the fitted line noticeably, so it is investigated before being kept.
Related terms
More Feature engineering data prep terms
- Correlation filter
- Count vectorizer
- Cyclical encoding
- Datetime features
- Discretization
- Domain knowledge features
- Dummy variable
- Dummy variable trap
Where you learn it
Cook's distance is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.