AI engineering glossary · ML fundamentals
What is validation set?
Validation set (also called Dev set, Development set): A portion of data kept apart from training and used to compare models and tune settings such as hyperparameters. Because decisions are made using it, it gradually stops being an unbiased check, which is why a separate final test set is still needed.
Validation set: an example
With 10,000 emails, 1,500 form a validation set used to decide whether a tree depth of 5 or 10 works better.
Related terms
More ML fundamentals terms
- VC dimension
- Weak supervision
- Ablation study
- Active learning
- Akaike information criterion
- Annotation
- Baseline model
- Bayesian information criterion
Where you learn it
Validation set is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.