Cost-sensitive machine learning

Sat, 18 Jul 2026 09:52:00 +0000

Definition

Cost-sensitive machine learning extends traditional supervised learning by assigning different penalties to different types of errors. In real-world scenarios, false positives and false negatives often have unequal consequences. This approach modifies loss functions or sampling strategies to minimize the total expected cost of predictions, making it essential for domains like fraud detection or medical diagnosis where error costs vary significantly.

Summary

A machine learning paradigm that incorporates misclassification costs into the training process to optimize for economic impact rather than just accuracy.

Loss Functions on English AI Terms Dictionary

Cost-sensitive machine learning

Definition

Summary