Glossary term
Glossary term
Foundations
In binary classification, one class is termed positive and the other is termed negative. The positive class is the thing or event that the model is testing for and the negative class is the other possibility. For example:
The negative class in a medical test might be "not tumor."
The negative class in an email classification model might be "not spam."
Contrast with positive class.
Created for this library
A fraud team labels legitimate transactions as the negative class so the model's task is to flag the rare positive cases.
A medical screening team labels healthy patients as the negative class and applies class weights to make rare positives matter during training.
A spam filter team labels non-spam emails as the negative class and tracks recall on the positive class to size operational impact.
Definition source: Google for Developers Machine Learning Glossary | Creative Commons Attribution 4.0 License