AI engineering glossary · ML fundamentals
What is early stopping?
Early stopping: A regularisation method for iterative training: watch the error on a validation set and stop when it has stopped improving for a set number of rounds, keeping the best version seen. It prevents the model from continuing to memorise training data after it has learned the general pattern.
Early stopping: an example
Training halts at epoch 34 because validation loss has not fallen for 5 epochs, and the epoch-29 weights are kept.
Related terms
More ML fundamentals terms
- Empirical risk minimisation
- Feature
- Feature space
- Generalisation
- Generalisation error
- Generalisation gap
- Generative model
- Grid search
Where you learn it
Early stopping is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.