AI engineering glossary · Feature engineering data prep
What is class imbalance?
Class imbalance (also called Imbalanced data, Imbalanced classes): A situation where one class in a classification dataset is far more common than another, as in fraud or disease detection. Models tend to favour the majority class, and accuracy becomes misleading, so special metrics and resampling are needed.
Class imbalance: an example
In a dataset of 1,00,000 transactions with 200 frauds (0.2 percent), a model that always says 'not fraud' is 99.8 percent accurate yet useless.
Related terms
More Feature engineering data prep terms
- Class weights
- Column transformer
- Constant feature
- Constant imputation
- Cook's distance
- Correlation filter
- Count vectorizer
- Cyclical encoding
Where you learn it
Class imbalance is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.