AI engineering glossary · ML fundamentals
What is cost-sensitive learning?
Cost-sensitive learning: Training or deciding in a way that treats different mistakes as having different costs, rather than counting all errors equally. It fits problems where missing a case costs far more than a false alarm.
Cost-sensitive learning: an example
Missing a cancer case is set to cost 20 times more than a false alarm, so the model is pushed to flag borderline scans.
Related terms
- Class imbalance
- Decision threshold
- Loss function
- Classification
More ML fundamentals terms
- Covariate shift
- Cross-validation
- Curse of dimensionality
- Data leakage
- Data snooping
- Data-centric AI
- Dataset
- Decision threshold
Where you learn it
Cost-sensitive learning is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.