AI engineering glossary · ML fundamentals
What is majority-class baseline?
Majority-class baseline (also called Zero-rule baseline): A baseline that always predicts the most frequent class in the training data. It shows how much accuracy comes free from class proportions alone, and reveals why a high accuracy number can be meaningless on skewed data.
Majority-class baseline: an example
If 90% of loan applicants repay, predicting 'repay' for everyone scores 90% accuracy without learning anything.
Related terms
More ML fundamentals terms
- Manifold hypothesis
- Meta-learning
- Model
- Model capacity
- Model selection
- Model variance
- Nested cross-validation
- No free lunch theorem
Where you learn it
Majority-class baseline is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.