AI engineering glossary · ML fundamentals
What is underfitting?
Underfitting: When a model is too simple or too little trained to capture the real pattern in the data, so it performs poorly even on its own training set. Fixes include using a more flexible model, adding informative features or reducing regularisation.
Underfitting: an example
Fitting a straight line to data that clearly follows a curve leaves large errors on both training and test data.
Related terms
More ML fundamentals terms
- Unsupervised learning
- Validation curve
- Validation set
- VC dimension
- Weak supervision
- Ablation study
- Active learning
- Akaike information criterion
Where you learn it
Underfitting is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.