AI engineering glossary · ML fundamentals
What is label?
Label (also called Target, Dependent variable, Response variable): The correct answer attached to a training example, which the model is asked to predict. For classification it is a category; for regression it is a number. Labels usually come from human annotation or recorded outcomes, and their quality places a ceiling on how good a supervised model can be.
Label: an example
In a set of X-ray images, each image is labelled 'pneumonia' or 'normal' by a radiologist; those tags are the labels.
Related terms
More ML fundamentals terms
- Label noise
- Latent variable
- Learning curve
- Leave-one-out cross-validation
- Linear separability
- Machine learning
- Majority-class baseline
- Manifold hypothesis
Where you learn it
Label is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.